{ "schema_version": "1.0", "count": 50, "items": [ { "id": "RES_0289B2007EA8", "resource_type": "skill", "canonical_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/lab-hardware-cad", "name": "lab-hardware-cad", "summary_en": "Design custom laboratory hardware as parametric build123d models and export fabrication-ready STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a research task needs a physical part that must mate with standardized labware, an optical table, a cage system, or a printer, CNC, or laser process.", "summary_zh": "以参数化build123d模型设计定制实验室硬件，并导出STEP、STL、DXF等制造文件，适用于需与标准实验室器具配合的物理部件。", "description_en": "This skill provides a procedural workflow for designing custom laboratory hardware as parametric build123d models and exporting fabrication-ready STEP, STL, and DXF files. It covers microfluidic chips, optomechanical mounts, labware adapters, tube racks, behavior rigs, and 3D-printed fixtures. Use when a research task requires a physical part that must mate with standardized labware, optical tables, or fabrication processes. The skill enforces a structured workflow including interface dimension verification and geometric checks, and requires running only trusted model files.", "description_zh": "该技能提供了一套程序化工作流程，用于将定制实验室硬件设计为参数化build123d模型，并导出可用于制造的STEP、STL和DXF文件。涵盖微流控芯片、光机支架、实验室器具适配器、试管架、行为装置和3D打印夹具。当研究任务需要与标准化实验室器具、光学平台或制造工艺配合的物理部件时使用。该技能强制执行结构化工作流程，包括接口尺寸验证和几何检查，并要求仅运行受信任的模型文件。", "provider_name": "K-Dense-AI", "homepage_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/lab-hardware-cad", "endpoint_url": null, "source_url": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/lab-hardware-cad/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "object.action" ], "categories": [ "search-research" ], "industries": [ "agriculture" ], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "original-only", "license": { "spdx_id": "MIT", "source": "https://github.com/K-Dense-AI/scientific-agent-skills/blob/1e5eeffbdad3749125afe7ab48a39694e27f181c/LICENSE" }, "github": { "repository": "K-Dense-AI/scientific-agent-skills", "owner": "K-Dense-AI", "path": "skills/lab-hardware-cad/SKILL.md", "commit": "1e5eeffbdad3749125afe7ab48a39694e27f181c", "stars": 42124, "forks": 3870, "updated_at": "2026-09-03T02:47:03Z" }, "skill": { "compatibility": "Python 3.10-3.14 with build123d 0.11.1 and matplotlib for snapshots. Geometry commands require build123d; the standards lookup and the interface check run on the standard library alone. No network access needed.", "allowed_tools": "Read Write Edit Bash Glob Grep", "content_hash": "36b730f5dd095eca8f7239fee85d12e088a861f63c5187e7d5297c448bb26fa2", "line_count": 390 }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:31:26.502Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": "search-research", "integrations": [ "GitHub" ], "use_cases": { "en": [ "Design custom lab hardware such as microfluidic chips and optomechanical mounts", "Export fabrication-ready STEP, STL, and DXF files for 3D printing or CNC", "Verify interface dimensions against published standards" ], "zh": [ "设计定制实验室硬件，如微流控芯片和光机支架", "导出可用于制造的STEP、STL和DXF文件，用于3D打印或CNC", "根据已发布标准验证接口尺寸" ] }, "categories": [ "search-research" ], "industries": [ "agriculture" ], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "1e5eeffbdad3", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "strong", "contract_completeness": "strong", "access_friction": "low", "operational_transparency": "strong", "evidence_strength": "source_inspected", "use_readiness": "ready_for_guidance", "reviewed_at": "2026-09-04T04:31:27.381Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T02:50:39.724Z", "last_seen_at": "2026-09-04T04:31:26.732Z", "published_at": "2026-09-03T06:25:07.945Z", "created_at": "2026-09-03T02:50:39.724Z", "updated_at": "2026-09-04T04:31:27.381Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_0289B2007EA8", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_0289B2007EA8/reviews", "public_url": "https://aiworkshub.io/resources/RES_0289B2007EA8", "distribution": { "canonical_identity": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/lab-hardware-cad", "syndicatable": true } }, { "id": "RES_03BB4E0BC815", "resource_type": "skill", "canonical_url": "https://github.com/bcmcpher/my-skills/tree/HEAD/plugins/stat-analysis/skills/plan-analysis", "name": "plan-analysis", "summary_en": "User describes a research question — what they're trying to predict or explain, what variables are involved, and what the study design looks like — and wants a recommended statistical model with a hierarchical test sequence from null to fully specified. Use this skill whenever the user asks which statistical test or mo", "summary_zh": "根据研究问题、变量及研究设计，推荐合适的统计模型，并提供从零模型到完整模型的层级检验序列。", "description_en": "This skill helps users select an appropriate statistical model and provides a hierarchical testing sequence from a null model to a fully specified model. It is intended for use when a user describes a research question, variables, and study design. 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Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.", "summary_zh": "记录架构决策与文档，适用于架构决策、公共API变更、功能发布及为未来工程师和代理记录代码库上下文时。", "description_en": "This Agent Skill provides guidance on recording decisions and documentation, including templates for Architecture Decision Records (ADRs), inline documentation, API documentation, README structure, changelog maintenance, and documentation for AI agents. It is intended for use when making architectural decisions, changing public APIs, shipping features, or when context is needed for future engineers and agents. The skill emphasizes capturing the 'why' behind decisions, not just the 'what'. It is sourced from a SKILL.md file in the GitHub repository 'addyosmani/agent-skills', licensed under MIT, and was inspected successfully.", "description_zh": "该代理技能提供记录决策和文档的指导，包括架构决策记录（ADR）、内联文档、API文档、README结构、变更日志维护以及面向AI代理的文档模板和最佳实践。适用于做出架构决策、更改公共API、发布功能或需要为未来工程师和代理提供上下文时。该技能强调记录决策背后的“为什么”，而不仅仅是“是什么”。来源是GitHub仓库“addyosmani/agent-skills”中的SKILL.md文件，采用MIT许可证，并已成功检查。", "provider_name": "addyosmani", "homepage_url": "https://github.com/addyosmani/agent-skills/tree/main/skills/documentation-and-adrs", "endpoint_url": null, "source_url": "https://raw.githubusercontent.com/addyosmani/agent-skills/d2c37ef6225dd8726cdd369a8030307f48592d26/skills/documentation-and-adrs/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "documentation.create", "documentation.update", "decision.record", "knowledge.organize" ], "categories": [ "search-research", "software-development" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "original-only", "license": { "spdx_id": "MIT", "source": "https://github.com/addyosmani/agent-skills/blob/d2c37ef6225dd8726cdd369a8030307f48592d26/LICENSE" }, "github": { "repository": "addyosmani/agent-skills", "owner": "addyosmani", "path": "skills/documentation-and-adrs/SKILL.md", "commit": "d2c37ef6225dd8726cdd369a8030307f48592d26", "stars": 91748, "forks": 9797, "updated_at": "2026-09-03T02:47:10Z" }, "skill": { "compatibility": null, "allowed_tools": null, "content_hash": "b867bb80fb681257c7625ae59a0dfd849b1fc0f0a2f0338e7923f38030df9793", "line_count": 289 }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:31:06.186Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": "search-research", "integrations": [ "GitHub" ], "use_cases": { "en": [ "Record architectural decisions using ADR templates", "Document public APIs and inline code rationale", "Maintain README and changelog for project context" ], "zh": [ "使用ADR模板记录架构决策", "记录公共API和内联代码的设计理由", "维护README和变更日志以提供项目上下文" ] }, "categories": [ "search-research", "software-development" ], "industries": [], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "d2c37ef6225d", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "strong", "evidence_strength": "source_inspected", "use_readiness": "ready_for_guidance", "reviewed_at": "2026-09-04T04:31:07.107Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T02:50:22.781Z", "last_seen_at": "2026-09-04T04:31:06.424Z", "published_at": "2026-09-03T06:25:02.076Z", "created_at": "2026-09-03T02:50:22.781Z", "updated_at": "2026-09-04T04:31:07.107Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_03BBC82EEBA0", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_03BBC82EEBA0/reviews", "public_url": "https://aiworkshub.io/resources/RES_03BBC82EEBA0", "distribution": { "canonical_identity": "https://github.com/addyosmani/agent-skills/tree/d2c37ef6225dd8726cdd369a8030307f48592d26/skills/documentation-and-adrs", "syndicatable": true } }, { "id": "RES_044D8CC64F52", "resource_type": "skill", "canonical_url": "https://github.com/TentacleOpera/switchboard/tree/HEAD/.agents/protocols/design-system-builder", "name": "design-system-builder", "summary_en": "Interactively build, derive, or refine a project's HTML design system via an agent interview", "summary_zh": "通过交互式访谈，为HTML项目构建、推导或优化设计系统。", "description_en": "This skill guides an agent through an interactive interview to build, derive, or refine a project's HTML design system. It is intended for design workflows where a structured design system is needed. The skill is available as a markdown file in the switchboard repository and requires no authentication.", "description_zh": "该技能通过交互式访谈，引导代理为HTML项目构建、推导或优化设计系统。适用于需要结构化设计系统的设计工作流。该技能以markdown文件形式存在于switchboard仓库中，无需认证即可使用。", "provider_name": "TentacleOpera", "homepage_url": "https://github.com/TentacleOpera/switchboard", "endpoint_url": null, "source_url": "https://github.com/TentacleOpera/switchboard/blob/d24d6499b6dfd24fa50803d29bc88b389eedc1c2/.agents/protocols/design-system-builder/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "design.system.build" ], "categories": [ "content-creative" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "MIT" }, "github": { "repository": "TentacleOpera/switchboard", "path": ".agents/protocols/design-system-builder/SKILL.md", "stars": 214 }, "skill": { "content_hash": "0a3cc5e95f459f7d" }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:30:39.268Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": "content-creative", "integrations": [ "GitHub" ], "use_cases": { "en": [ "Build a new HTML design system for a project", "Derive a design system from existing HTML", "Refine an existing design system" ], "zh": [ "为项目构建新的HTML设计系统", "从现有HTML中推导设计系统", "优化现有的设计系统" ] }, "categories": [ "content-creative" ], "industries": [], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "d24d6499b6df", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "partial", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-04T04:30:41.281Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T13:46:19.733Z", "last_seen_at": "2026-09-04T04:30:39.521Z", "published_at": "2026-09-03T13:46:19.733Z", "created_at": "2026-09-03T13:46:19.733Z", "updated_at": "2026-09-04T04:30:41.281Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_044D8CC64F52", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_044D8CC64F52/reviews", "public_url": "https://aiworkshub.io/resources/RES_044D8CC64F52", "distribution": { "canonical_identity": "https://github.com/TentacleOpera/switchboard/tree/HEAD/.agents/protocols/design-system-builder", "syndicatable": true } }, { "id": "RES_04B935678DEA", "resource_type": "skill", "canonical_url": "https://github.com/wshobson/agents/tree/a30778f8c4e6b0a87567941b7cca4f534bf642b6/plugins/backend-development/skills/workflow-orchestration-patterns", "name": "workflow-orchestration-patterns", "summary_en": "Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.", "summary_zh": "使用Temporal设计持久工作流，涵盖工作流与活动分离、Saga模式、状态管理和确定性约束，适用于构建长时间运行的分布式流程。", "description_en": "This skill provides advisory guidance on designing durable workflows with Temporal, covering workflow vs activity separation, saga patterns, state management, and determinism constraints. It is intended for building long-running processes, distributed transactions, or microservice orchestration. The skill is purely advisory and declares no executable tools or APIs.", "description_zh": "该技能提供使用Temporal设计持久工作流的咨询指导，涵盖工作流与活动分离、Saga模式、状态管理和确定性约束。适用于构建长时间运行的流程、分布式事务或微服务编排。该技能纯属咨询性质，未声明任何可执行工具或API。", "provider_name": "wshobson", "homepage_url": "https://github.com/wshobson/agents/tree/main/plugins/backend-development/skills/workflow-orchestration-patterns", "endpoint_url": null, "source_url": "https://raw.githubusercontent.com/wshobson/agents/a30778f8c4e6b0a87567941b7cca4f534bf642b6/plugins/backend-development/skills/workflow-orchestration-patterns/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "software.development", "software.architecture", "software.best-practices" ], "categories": [ "software-development" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "original-only", "license": { "spdx_id": "MIT", "source": "https://github.com/wshobson/agents/blob/a30778f8c4e6b0a87567941b7cca4f534bf642b6/LICENSE" }, "github": { "repository": "wshobson/agents", "owner": "wshobson", "path": "plugins/backend-development/skills/workflow-orchestration-patterns/SKILL.md", "commit": "a30778f8c4e6b0a87567941b7cca4f534bf642b6", "stars": 39366, "forks": 4194, "updated_at": "2026-09-03T02:19:37Z" }, "skill": { "compatibility": null, "allowed_tools": null, "content_hash": "f4418f98189bd89d7b801ec65df48b53caa1c555a23f1d9684799415818f1024", "line_count": 99 }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:30:16.841Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": "software-development", "integrations": [ "GitHub" ], "use_cases": { "en": [ "Design durable workflows with Temporal for distributed systems", "Implement saga patterns and manage state in long-running processes" ], "zh": [ "使用Temporal为分布式系统设计持久工作流", "在长时间运行的流程中实现Saga模式和管理状态" ] }, "categories": [ "software-development" ], "industries": [], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "a30778f8c4e6", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "strong", "evidence_strength": "source_inspected", "use_readiness": "ready_for_guidance", "reviewed_at": "2026-09-04T04:30:17.717Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T02:51:07.577Z", "last_seen_at": "2026-09-04T04:30:17.068Z", "published_at": "2026-09-03T06:24:52.843Z", "created_at": "2026-09-03T02:51:07.577Z", "updated_at": "2026-09-04T04:30:17.717Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_04B935678DEA", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_04B935678DEA/reviews", "public_url": "https://aiworkshub.io/resources/RES_04B935678DEA", "distribution": { "canonical_identity": "https://github.com/wshobson/agents/tree/a30778f8c4e6b0a87567941b7cca4f534bf642b6/plugins/backend-development/skills/workflow-orchestration-patterns", "syndicatable": true } }, { "id": "RES_04CF577D2FA9", "resource_type": "skill", "canonical_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/bulk-rnaseq", "name": "bulk-rnaseq", "summary_en": "End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathway-enrichment), and publication figures (scientific-visualization). Use whenever the user has bulk RNA-seq reads or quant output and wants a complete, reproducible differential-expression workflow — e.g. \"analyze my RNA-seq\", \"FASTQ to DESeq2\", \"run nf-core/rnaseq\", \"STAR/Salmon quantification\", \"build a counts matrix for DESeq2\", or \"go from reads to differentially expressed genes and enriched pathways\". Routes between an nf-core/rnaseq (Nextflow) path and a standalone STAR/Salmon path, and covers experimental design, strandedness, and QC gates. For single-cell RNA-seq use the scanpy skill instead.", "summary_zh": "端到端批量RNA-seq分析编排，从FASTQ到差异表达与通路富集。", "description_en": "This skill orchestrates a complete bulk RNA-seq differential-expression workflow, from raw FASTQ reads through QC, trimming, alignment, and quantification to a gene-level counts matrix, then hands off to downstream skills for differential expression, pathway enrichment, and figure generation. It supports both an nf-core/rnaseq (Nextflow) path and a standalone STAR/Salmon path, and includes guidance on experimental design and QC. The skill is intended for users with bulk RNA-seq data who want a reproducible analysis; for single-cell data, the scanpy skill should be used instead.", "description_zh": "该技能编排完整的批量RNA-seq差异表达工作流，从原始FASTQ读段经过QC、修剪、比对和定量，生成基因水平计数矩阵，然后移交给下游技能进行差异表达、通路富集和图表生成。它支持nf-core/rnaseq（Nextflow）路径和独立STAR/Salmon路径，并包含实验设计和QC指导。该技能适用于拥有批量RNA-seq数据并希望进行可复现分析的用户；对于单细胞数据，应改用scanpy技能。", "provider_name": "K-Dense-AI", "homepage_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/bulk-rnaseq", "endpoint_url": null, "source_url": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/bulk-rnaseq/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "object.action" ], "categories": [], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "original-only", "license": { "spdx_id": "MIT", "source": "https://github.com/K-Dense-AI/scientific-agent-skills/blob/1e5eeffbdad3749125afe7ab48a39694e27f181c/LICENSE" }, "github": { "repository": "K-Dense-AI/scientific-agent-skills", "owner": "K-Dense-AI", "path": "skills/bulk-rnaseq/SKILL.md", "commit": "1e5eeffbdad3749125afe7ab48a39694e27f181c", "stars": 42124, "forks": 3870, "updated_at": "2026-09-03T02:47:03Z" }, "skill": { "compatibility": null, "allowed_tools": null, "content_hash": "d1ec11577f5693a2490abd53e31ef83799358d6da1e44a1769636823565e68f7", "line_count": 216 }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:30:09.479Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": null, "integrations": [ "GitHub" ], "use_cases": { "en": [ "Run a complete bulk RNA-seq differential expression analysis from raw FASTQ files.", "Generate a gene-level counts matrix from STAR, Salmon, or featureCounts output for DESeq2.", "Configure and run nf-core/rnaseq pipeline for reproducible RNA-seq analysis." ], "zh": [ "从原始FASTQ文件运行完整的批量RNA-seq差异表达分析。", "从STAR、Salmon或featureCounts输出生成用于DESeq2的基因水平计数矩阵。", "配置并运行nf-core/rnaseq流程，实现可复现的RNA-seq分析。" ] }, "categories": [], "industries": [], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "1e5eeffbdad3", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "strong", "contract_completeness": "strong", "access_friction": "low", "operational_transparency": "strong", "evidence_strength": "source_inspected", "use_readiness": "ready_for_guidance", "reviewed_at": "2026-09-04T04:30:10.392Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T02:50:29.774Z", "last_seen_at": "2026-09-04T04:30:09.721Z", "published_at": "2026-09-03T06:24:55.069Z", "created_at": "2026-09-03T02:50:29.774Z", "updated_at": "2026-09-04T04:30:10.392Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_04CF577D2FA9", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_04CF577D2FA9/reviews", "public_url": "https://aiworkshub.io/resources/RES_04CF577D2FA9", "distribution": { "canonical_identity": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/bulk-rnaseq", "syndicatable": true } }, { "id": "RES_0515A58CD48A", "resource_type": "skill", "canonical_url": "https://github.com/sebbsssss/clude/tree/HEAD/", "name": "Clude Memory MCP", "summary_en": "MCP server for Clude's cognitive memory system — store, recall, search, and dream. Supports hosted (zero-setup), self-hosted (Supabase + pgvector), and local (offline) modes.", "summary_zh": "为Clude认知记忆系统提供MCP服务器，支持记忆的存储、召回、搜索与梦境操作，可托管、自托管或本地部署。", "description_en": "This skill provides an MCP server for Clude's cognitive memory system, enabling storage, recall, search, and dream operations on memories. It supports hosted, self-hosted (Supabase + pgvector), and local offline modes. The skill is distributed as a GitHub repository under the MIT license, but no runtime authentication or pricing details are provided in the evidence.", "description_zh": "该技能为Clude的认知记忆系统提供MCP服务器，支持对记忆进行存储、召回、搜索和梦境操作。它支持托管、自托管（基于Supabase和pgvector）以及本地离线模式。该技能以GitHub仓库形式分发，采用MIT许可证，但证据中未提供运行时认证或定价详情。", "provider_name": "sebbsssss", "homepage_url": "https://github.com/sebbsssss/clude", "endpoint_url": null, "source_url": "https://github.com/sebbsssss/clude/blob/cecf234f10397b1e21dec2ff65ded864982f3564/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "memory.store", "memory.recall", "memory.search", "memory.dream" ], "categories": [ "data-analytics" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "MIT" }, "github": { "repository": "sebbsssss/clude", "path": "SKILL.md", "stars": 21 }, "skill": { "content_hash": "7d2a625de70ab921" }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:30:01.382Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": "data-analytics", "integrations": [ "GitHub" ], "use_cases": { "en": [ "Store and recall memories for AI agents", "Search across stored memories", "Run dream operations on memory data" ], "zh": [ "为AI代理存储和召回记忆", "在存储的记忆中进行搜索", "对记忆数据执行梦境操作" ] }, "categories": [ "data-analytics" ], "industries": [], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "cecf234f1039", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "partial", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "weak", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-04T04:30:02.329Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T13:46:17.779Z", "last_seen_at": "2026-09-04T04:30:01.642Z", "published_at": "2026-09-03T13:46:17.779Z", "created_at": "2026-09-03T13:46:17.779Z", "updated_at": "2026-09-04T04:30:02.329Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_0515A58CD48A", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_0515A58CD48A/reviews", "public_url": "https://aiworkshub.io/resources/RES_0515A58CD48A", "distribution": { "canonical_identity": "https://github.com/sebbsssss/clude/tree/HEAD/", "syndicatable": true } }, { "id": "RES_04DDB426DA87", "resource_type": "skill", "canonical_url": "https://github.com/wshobson/agents/tree/a30778f8c4e6b0a87567941b7cca4f534bf642b6/plugins/data-engineering/skills/data-quality-frameworks", "name": "data-quality-frameworks", "summary_en": "Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.", "summary_zh": "使用Great Expectations、dbt测试和数据契约实施数据质量验证，适用于构建数据管道、制定验证规则及建立数据契约。", "description_en": "This Agent Skill provides guidance and patterns for implementing data quality validation using Great Expectations, dbt tests, and data contracts. It is designed for use when building data quality pipelines, implementing validation rules, or establishing data contracts. 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Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, visualization, and converting R-friendly single-cell formats such as Seurat or SingleCellExperiment RDS files into h5ad for Scanpy. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.", "summary_zh": "标准单细胞RNA-seq分析流程，涵盖质控、归一化、降维、聚类、差异表达及可视化，并支持将R格式数据转换为h5ad。", "description_en": "This Agent Skill provides a standard single-cell RNA-seq analysis pipeline using Scanpy, covering quality control, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, visualization, and conversion of R-friendly single-cell formats (Seurat or SingleCellExperiment RDS files) to h5ad. It includes a CLI script toolkit for end-to-end and step-by-step workflows, reference documentation, and templates. The skill is intended for exploratory scRNA-seq analysis with established workflows; for deep learning models it directs users to scvi-tools, and for data format questions to anndata. 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Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.", "summary_zh": "使用 PyTorch Lightning 组织代码、配置 Trainer 进行多 GPU/TPU 训练，实现数据管道、回调、日志和分布式训练，用于可扩展的神经网络训练。", "description_en": "This skill provides procedural knowledge for using PyTorch Lightning to structure and scale deep learning training. It covers organizing PyTorch code into LightningModules, configuring Trainers for multi-GPU/TPU training, implementing data pipelines with LightningDataModules, using callbacks, integrating experiment loggers (TensorBoard, W&B, MLflow, Comet, CSV), and applying distributed training strategies (DDP, FSDP, DeepSpeed). The skill includes templates and reference documentation for common patterns and best practices. It is intended for software development, testing, data analysis, scientific research, document processing, writing, DevOps, and agent orchestration tasks.", "description_zh": "该技能提供了使用 PyTorch Lightning 构建和扩展深度学习训练的程序性知识。涵盖将 PyTorch 代码组织为 LightningModule、配置 Trainer 以进行多 GPU/TPU 训练、使用 LightningDataModule 实现数据管道、使用回调、集成实验记录器（TensorBoard、W&B、MLflow、Comet、CSV）以及应用分布式训练策略（DDP、FSDP、DeepSpeed）。技能包含常见模式和最佳实践的模板及参考文档。适用于软件开发、测试、数据分析、科学研究、文档处理、写作、DevOps 和代理编排任务。", "provider_name": "K-Dense-AI", "homepage_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/pytorch-lightning", "endpoint_url": null, "source_url": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/pytorch-lightning/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "skill.pytorch-lightning.train", "skill.pytorch-lightning.organize-model", "skill.pytorch-lightning.configure-trainer", "skill.pytorch-lightning.data-pipeline", "skill.pytorch-lightning.callbacks", "skill.pytorch-lightning.logging", "skill.pytorch-lightning.distributed-training" ], "categories": [ "ai-models", "data-analytics", "search-research", "software-development" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "original-only", "license": { "spdx_id": "MIT", "source": "https://github.com/K-Dense-AI/scientific-agent-skills/blob/1e5eeffbdad3749125afe7ab48a39694e27f181c/LICENSE" }, "github": { "repository": "K-Dense-AI/scientific-agent-skills", "owner": "K-Dense-AI", "path": "skills/pytorch-lightning/SKILL.md", "commit": "1e5eeffbdad3749125afe7ab48a39694e27f181c", "stars": 42124, "forks": 3870, "updated_at": "2026-09-03T02:47:03Z" }, "skill": { "compatibility": "Requires Python 3.10+ and lightning 2.6+ (or pytorch-lightning 2.6+). GPU training needs CUDA-capable PyTorch. Optional loggers (wandb, mlflow, comet-ml) and DeepSpeed require separate installs.", "allowed_tools": "Read Write Edit Bash", "content_hash": "eacd09ffc22ab266c385b4897136636dbaee15fe62dc8cec2264e7fa4f557810", "line_count": 208 }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:28:23.583Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": "ai-models", "integrations": [ "GitHub" ], "use_cases": { "en": [ "Organize PyTorch code into LightningModules for scalable training.", "Configure Trainers for multi-GPU/TPU training with DDP, FSDP, or DeepSpeed.", "Implement data pipelines with LightningDataModules and integrate experiment loggers." ], "zh": [ "将 PyTorch 代码组织为 LightningModule 以进行可扩展训练。", "配置 Trainer 以使用 DDP、FSDP 或 DeepSpeed 进行多 GPU/TPU 训练。", "使用 LightningDataModule 实现数据管道并集成实验记录器。" ] }, "categories": [ "ai-models", "data-analytics", "search-research", "software-development" ], "industries": [], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "1e5eeffbdad3", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "strong", "contract_completeness": "strong", "access_friction": "low", "operational_transparency": "strong", "evidence_strength": "source_inspected", "use_readiness": "ready_for_guidance", "reviewed_at": "2026-09-04T04:28:24.771Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T02:50:52.731Z", "last_seen_at": "2026-09-04T04:28:23.795Z", "published_at": "2026-09-03T06:24:24.412Z", "created_at": "2026-09-03T02:50:52.731Z", "updated_at": "2026-09-04T04:28:24.771Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_0E9CED83E8A1", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_0E9CED83E8A1/reviews", "public_url": "https://aiworkshub.io/resources/RES_0E9CED83E8A1", "distribution": { "canonical_identity": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/pytorch-lightning", "syndicatable": true } }, { "id": "RES_0E2E977A086F", "resource_type": "skill", "canonical_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/neuropixels-analysis", "name": "neuropixels-analysis", "summary_en": "Analyze Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.", "summary_zh": "使用 SpikeInterface 端到端分析 Neuropixels 细胞外记录，涵盖预处理、尖峰排序、质量评估与单元筛选。", "description_en": "This skill provides a comprehensive workflow for analyzing Neuropixels extracellular recordings using SpikeInterface. It covers loading data from SpikeGLX, Open Ephys, and NWB formats; preprocessing; drift detection and motion correction; spike sorting with Kilosort4 and CPU alternatives; computing quality metrics; and unit curation via threshold-based, model-based, and AI-assisted methods. It requires Python 3.10+ and SpikeInterface dependencies, and is designed for Neuropixels 1.0 and 2.0 probes.", "description_zh": "该技能提供了使用 SpikeInterface 分析 Neuropixels 细胞外记录的综合工作流程。涵盖从 SpikeGLX、Open Ephys 和 NWB 格式加载数据；预处理；漂移检测和运动校正；使用 Kilosort4 及 CPU 替代方案进行尖峰排序；计算质量指标；以及通过基于阈值、基于模型和 AI 辅助的方法进行单元筛选。它需要 Python 3.10+ 和 SpikeInterface 依赖，专为 Neuropixels 1.0 和 2.0 探针设计。", "provider_name": "K-Dense-AI", "homepage_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/neuropixels-analysis", "endpoint_url": null, "source_url": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/neuropixels-analysis/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "data.analyze", "data.transform", "data.generate" ], "categories": [ "data-analytics" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "original-only", "license": { "spdx_id": "MIT", "source": "https://github.com/K-Dense-AI/scientific-agent-skills/blob/1e5eeffbdad3749125afe7ab48a39694e27f181c/LICENSE" }, "github": { "repository": "K-Dense-AI/scientific-agent-skills", "owner": "K-Dense-AI", "path": "skills/neuropixels-analysis/SKILL.md", "commit": "1e5eeffbdad3749125afe7ab48a39694e27f181c", "stars": 42124, "forks": 3870, "updated_at": "2026-09-03T02:47:03Z" }, "skill": { "compatibility": null, "allowed_tools": null, "content_hash": "3eadefe63c2724f5be4e981e07d818a9c9f8daada26ed3e587feeb5e9455b6fb", "line_count": 430 }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:27:59.408Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": "data-analytics", "integrations": [ "GitHub" ], "use_cases": { "en": [ "Load and preprocess Neuropixels recordings from SpikeGLX, Open Ephys, or NWB formats.", "Perform spike sorting with Kilosort4 or CPU alternatives and compute quality metrics.", "Curate units using threshold-based, model-based, or AI-assisted methods." ], "zh": [ "从 SpikeGLX、Open Ephys 或 NWB 格式加载并预处理 Neuropixels 记录。", "使用 Kilosort4 或 CPU 替代方案进行尖峰排序并计算质量指标。", "使用基于阈值、基于模型或 AI 辅助的方法筛选单元。" ] }, "categories": [ "data-analytics" ], "industries": [], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "1e5eeffbdad3", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": "No suspicious or malicious evidence.", "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "strong", "contract_completeness": "strong", "access_friction": "low", "operational_transparency": "strong", "evidence_strength": "source_inspected", "use_readiness": "ready_for_guidance", "reviewed_at": "2026-09-04T04:28:00.322Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T02:50:44.193Z", "last_seen_at": "2026-09-04T04:27:59.628Z", "published_at": "2026-09-03T06:24:25.270Z", "created_at": "2026-09-03T02:50:44.193Z", "updated_at": "2026-09-04T04:28:00.322Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_0E2E977A086F", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_0E2E977A086F/reviews", "public_url": "https://aiworkshub.io/resources/RES_0E2E977A086F", "distribution": { "canonical_identity": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/neuropixels-analysis", "syndicatable": true } }, { "id": "RES_00071EE04EBB", "resource_type": "skill", "canonical_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/omero-integration", "name": "omero-integration", "summary_en": "Securely inspect and automate microscopy data workflows against OMERO.server with omero-py, BlitzGateway, OMERO CLI, tables, annotations, ROIs, rendering, and documented OMERO.web APIs. Use for scoped OMERO inventory, metadata export, import/export planning, or reviewed write workflows.", "summary_zh": "安全地检查并自动化OMERO.server显微镜数据工作流，支持元数据导出、导入导出规划及经审查的写入操作。", "description_en": "This Agent Skill provides a procedural guide for interacting with OMERO.server, a microscopy data management platform. It covers secure connection practices, data inspection, metadata export, and planning of import/export operations. The skill emphasizes bounded operations, credential safety, and use of documented APIs and client libraries. It includes bundled helper scripts for validation, inventory, metadata export, and transfer planning, all designed to be safe and require explicit execution for remote operations.", "description_zh": "该Agent技能提供了与OMERO.server（显微镜数据管理平台）交互的程序性指南。涵盖安全连接实践、数据检查、元数据导出以及导入/导出操作的规划。技能强调有界操作、凭据安全以及使用文档化的API和客户端库。它包含用于验证、清单、元数据导出和传输规划的捆绑辅助脚本，这些脚本设计为安全，并要求显式执行远程操作。", "provider_name": "K-Dense-AI", "homepage_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/omero-integration", "endpoint_url": null, "source_url": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/omero-integration/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "data.read", "data.write", "data.export", "data.import", "data.inventory", "data.metadata", "data.rendering", "data.roi", "data.table", "data.annotation", "data.connection", "data.security", "data.planning" ], "categories": [ "data-analytics" ], "industries": [ "health" ], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "original-only", "license": { "spdx_id": "MIT", "source": "https://github.com/K-Dense-AI/scientific-agent-skills/blob/1e5eeffbdad3749125afe7ab48a39694e27f181c/LICENSE" }, "github": { "repository": "K-Dense-AI/scientific-agent-skills", "owner": "K-Dense-AI", "path": "skills/omero-integration/SKILL.md", "commit": "1e5eeffbdad3749125afe7ab48a39694e27f181c", "stars": 42124, "forks": 3870, "updated_at": "2026-09-03T02:47:03Z" }, "skill": { "compatibility": ">-", "allowed_tools": null, "content_hash": "242ba431ebc6d04d06b9e37ee370896e3339bcd0a0e69186d8693ad058a9515d", "line_count": 240 }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:26:49.101Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": "data-analytics", "integrations": [ "GitHub" ], "use_cases": { "en": [ "Inspect microscopy data inventories and metadata on OMERO.server", "Export image metadata and annotations in a bounded, read-only manner", "Plan import/export operations with local dry-run helpers" ], "zh": [ "在OMERO.server上检查显微镜数据清单和元数据", "以有界、只读方式导出图像元数据和注释", "使用本地试运行助手规划导入/导出操作" ] }, "categories": [ "data-analytics" ], "industries": [ "health" ], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "1e5eeffbdad3", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "strong", "contract_completeness": "strong", "access_friction": "low", "operational_transparency": "strong", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-04T04:26:50.147Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T02:50:44.199Z", "last_seen_at": "2026-09-04T04:26:49.364Z", "published_at": "2026-09-03T06:25:41.697Z", "created_at": "2026-09-03T02:50:44.199Z", "updated_at": "2026-09-04T04:26:50.147Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_00071EE04EBB", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_00071EE04EBB/reviews", "public_url": "https://aiworkshub.io/resources/RES_00071EE04EBB", "distribution": { "canonical_identity": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/omero-integration", "syndicatable": true } }, { "id": "RES_000EB40E71DE", "resource_type": "skill", "canonical_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/polars-bio", "name": "polars-bio", "summary_en": "High-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames. Overlap, nearest, merge, coverage, complement, subtract for BED/VCF/BAM/GFF intervals. Streaming, cloud-native, faster bioframe alternative.", "summary_zh": "基于Polars的高性能基因组区间操作与生物信息学文件读写技能，支持流式处理与云存储。", "description_en": "This skill provides high-performance genomic interval operations (overlap, nearest, merge, coverage, complement, subtract) and bioinformatics file I/O (BED, VCF, BAM, CRAM, GFF/GTF, FASTA, FASTQ, SAM) on Polars DataFrames. It supports streaming/out-of-core processing, cloud-native file I/O (S3, GCS, Azure), and SQL queries via DataFusion. Use it for large-scale genomic data analysis that requires speed and scalability. Requires Python 3.11-3.14 and the polars-bio library.", "description_zh": "该技能提供基于Polars DataFrame的高性能基因组区间操作（overlap、nearest、merge、coverage、complement、subtract）和生物信息学文件读写（BED、VCF、BAM、CRAM、GFF/GTF、FASTA、FASTQ、SAM）。支持流式/核外处理、云原生文件I/O（S3、GCS、Azure）以及通过DataFusion的SQL查询。适用于需要速度和可扩展性的大规模基因组数据分析。需要Python 3.11-3.14和polars-bio库。", "provider_name": "K-Dense-AI", "homepage_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/polars-bio", "endpoint_url": null, "source_url": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/polars-bio/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "genomic.interval.operations", "bioinformatics.file.io", "data.sql.query", "data.streaming.processing", "data.cloud.io" ], "categories": [ "data-analytics" ], "industries": [ "health" ], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "original-only", "license": { "spdx_id": "Apache-2.0", "source": "https://github.com/K-Dense-AI/scientific-agent-skills/blob/1e5eeffbdad3749125afe7ab48a39694e27f181c/LICENSE" }, "github": { "repository": "K-Dense-AI/scientific-agent-skills", "owner": "K-Dense-AI", "path": "skills/polars-bio/SKILL.md", "commit": "1e5eeffbdad3749125afe7ab48a39694e27f181c", "stars": 42124, "forks": 3870, "updated_at": "2026-09-03T02:47:03Z" }, "skill": { "compatibility": "Requires Python 3.11–3.14 and polars-bio (uv pip install). Cloud I/O uses standard AWS/GCS/Azure SDK env vars when paths use s3://, gs://, or az:// URIs.", "allowed_tools": "Read Write Edit Bash", "content_hash": "2dd655de40d2ba1debacb136cfb1df22d4c22246142ba316b418b3b6a5ca9a09", "line_count": 397 }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:26:48.509Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": "data-analytics", "integrations": [ "GitHub" ], "use_cases": { "en": [ "Perform genomic interval operations such as overlap, nearest, and merge on large datasets.", "Read and write bioinformatics file formats including BED, VCF, BAM, and GFF.", "Run SQL queries on genomic data files using DataFusion." ], "zh": [ "对大规模数据集执行基因组区间操作，如overlap、nearest和merge。", "读写生物信息学文件格式，包括BED、VCF、BAM和GFF。", "使用DataFusion对基因组数据文件运行SQL查询。" ] }, "categories": [ "data-analytics" ], "industries": [ "health" ], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "1e5eeffbdad3", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "strong", "contract_completeness": "strong", "access_friction": "low", "operational_transparency": "strong", "evidence_strength": "source_inspected", "use_readiness": "ready_for_guidance", "reviewed_at": "2026-09-04T04:26:49.463Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T02:50:48.846Z", "last_seen_at": "2026-09-04T04:26:48.736Z", "published_at": "2026-09-03T06:25:39.569Z", "created_at": "2026-09-03T02:50:48.846Z", "updated_at": "2026-09-04T04:26:49.463Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_000EB40E71DE", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_000EB40E71DE/reviews", "public_url": "https://aiworkshub.io/resources/RES_000EB40E71DE", "distribution": { "canonical_identity": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/polars-bio", "syndicatable": true } }, { "id": "RES_0665F9B77E90", "resource_type": "skill", "canonical_url": "https://github.com/enriqueescobar-it/linktreeprofiles/tree/HEAD/SKILL/notion-task-creator", "name": "notion-task-creator", "summary_en": "Adds a new task to a project's Tasks board in the user's Notion Agent Workspace (Projects → the project → Tasks). Use whenever the user asks to add/create a task for a specific project, or a general task not tied to any project (goes under Projects → General Tasks). Requires the connected Notion MCP server.", "summary_zh": "在用户的 Notion 工作区中为指定项目或通用任务创建任务，需连接 Notion MCP 服务器。", "description_en": "This skill adds a new task to a project's Tasks board in the user's Notion Agent Workspace, either under a specific project or under General Tasks. It is intended for use when the user asks to add or create a task. The skill requires a connected Notion MCP server to function.", "description_zh": "该技能用于在用户的 Notion 智能工作区中，为指定项目或通用任务添加新任务。当用户要求添加或创建任务时使用。该技能需要已连接的 Notion MCP 服务器才能运行。", "provider_name": "enriqueescobar-it", "homepage_url": "https://github.com/enriqueescobar-it/linktreeprofiles", "endpoint_url": null, "source_url": "https://github.com/enriqueescobar-it/linktreeprofiles/blob/ff905decb832e25c069e7ec0ba2f66be0586e184/SKILL/notion-task-creator/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "task.create" ], "categories": [], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "MIT" }, "github": { "repository": "enriqueescobar-it/linktreeprofiles", "path": "SKILL/notion-task-creator/SKILL.md", "stars": 0 }, "skill": { "content_hash": "c94c7b32ccbf855a" }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:17:35.526Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": null, "integrations": [ "GitHub", "Notion" ], "use_cases": { "en": [ "Add a task to a specific project's Tasks board", "Add a general task not tied to any project" ], "zh": [ "向特定项目的任务看板添加任务", "添加与任何项目无关的通用任务" ] }, "categories": [], "industries": [], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "ff905decb832", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "partial", "contract_completeness": "natural_language", "access_friction": "medium", "operational_transparency": "weak", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-04T04:17:36.367Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T13:46:27.080Z", "last_seen_at": "2026-09-04T04:17:35.755Z", "published_at": "2026-09-03T13:46:27.080Z", "created_at": "2026-09-03T13:46:27.080Z", "updated_at": "2026-09-04T04:17:36.367Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_0665F9B77E90", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_0665F9B77E90/reviews", "public_url": "https://aiworkshub.io/resources/RES_0665F9B77E90", "distribution": { "canonical_identity": "https://github.com/enriqueescobar-it/linktreeprofiles/tree/HEAD/SKILL/notion-task-creator", "syndicatable": true } }, { "id": "RES_07259F0B8068", "resource_type": "skill", "canonical_url": "https://github.com/Cocoanetics/SwiftButler/tree/HEAD/", "name": "swiftbutler", "summary_en": "Analyze, syntax-check, reindent, and distribute Swift source code with the SwiftButler CLI. 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It is designed for use in academic writing workflows where documents are edited in Word format. The skill is freely available under the MIT license and requires no authentication.", "description_zh": "该技能用于在docx文件中插入、格式化学术引用，并支持交叉引用和多种参考文献样式。它适用于需要编辑Word格式文档的学术写作流程。该技能以MIT许可证免费提供，无需身份验证。", "provider_name": "fuwenhao12", "homepage_url": "https://github.com/fuwenhao12/academic-ref-inserter", "endpoint_url": null, "source_url": "https://github.com/fuwenhao12/academic-ref-inserter/blob/dfa079ec9be76d30a2053522fdc8bb7fc986c136/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "document.citation-insert", "document.citation-format", "document.citation-cross-reference" ], "categories": [], "industries": [ "education" ], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "zh", "translation_status": "ai-translated", "license": { "spdx_id": "MIT" }, "github": { "repository": "fuwenhao12/academic-ref-inserter", "path": "SKILL.md", "commit": "dfa079ec9be76d30a2053522fdc8bb7fc986c136", "stars": 55, "updated_at": "2026-08-11T15:17:40Z" }, "skill": { "content_hash": "155b6cba788d50edc2bf5c9210766250433ac6386832170b23ec23a4d76dafc0" }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:17:08.010Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": null, "integrations": [ "GitHub" ], "use_cases": { "en": [ "Insert academic citations into Word documents", "Format citations according to various bibliography styles", "Cross-reference citations within a document" ], "zh": [ "在Word文档中插入学术引用", "根据多种参考文献样式格式化引用", "在文档内交叉引用文献" ] }, "categories": [], "industries": [ "education" ], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "dfa079ec9be7", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "partial", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "weak", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-04T04:17:08.915Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T12:10:41.569Z", "last_seen_at": "2026-09-04T04:17:08.265Z", "published_at": "2026-09-03T12:10:41.569Z", "created_at": "2026-09-03T12:10:41.569Z", "updated_at": "2026-09-04T04:17:08.915Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_07AD9D0E1D2D", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_07AD9D0E1D2D/reviews", "public_url": "https://aiworkshub.io/resources/RES_07AD9D0E1D2D", "distribution": { "canonical_identity": "https://github.com/fuwenhao12/academic-ref-inserter", "syndicatable": true } }, { "id": "RES_083C499BE257", "resource_type": "skill", "canonical_url": "https://github.com/majiayu000/claude-skill-registry/tree/HEAD/skills/domains/distress-screening", "name": "distress-screening", "summary_en": "Screen for psychological distress and track symptom burden using K6 and K10 scales.", "summary_zh": "使用K6和K10量表筛查心理困扰并跟踪症状负担，适用于临床或健康场景中的心理评估。", "description_en": "This skill screens for psychological distress using the K6 and K10 scales and tracks symptom burden over time. It is suitable for clinical or health-related contexts where mental health assessment is needed. The skill is distributed as a free, open-source (MIT) Agent Skill, and no authentication is required.", "description_zh": "该技能使用K6和K10量表筛查心理困扰，并随时间跟踪症状负担。适用于需要心理健康评估的临床或健康相关场景。该技能以免费、开源（MIT）的Agent Skill形式分发，无需身份验证。", "provider_name": "majiayu000", "homepage_url": "https://github.com/majiayu000/claude-skill-registry", "endpoint_url": null, "source_url": "https://github.com/majiayu000/claude-skill-registry/blob/8929dcba0964653ab807d28d1c1df10eb706f7d2/skills/domains/distress-screening/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "health.screening" ], "categories": [], "industries": [ "health" ], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "ai-translated", "license": { "spdx_id": "MIT" }, "github": { "repository": "majiayu000/claude-skill-registry", "path": "skills/domains/distress-screening/SKILL.md", "commit": "8929dcba0964653ab807d28d1c1df10eb706f7d2", "stars": 590, "updated_at": "2026-09-03T07:02:33Z" }, "skill": { "content_hash": "720d2470464dab9ba94fc9a7f930ae1bd9ca69982fa53a2da295ce9621002754" }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T04:16:54.879Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": null, "integrations": [ "GitHub" ], "use_cases": { "en": [ "Screen patients for psychological distress using K6 or K10 scales.", "Track symptom burden over time for ongoing mental health monitoring." ], "zh": [ "使用K6或K10量表对患者进行心理困扰筛查。", "持续跟踪症状负担，用于心理健康监测。" ] }, "categories": [], "industries": [ "health" ], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "8929dcba0964", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "partial", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "weak", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-04T04:16:55.724Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T12:11:42.996Z", "last_seen_at": "2026-09-04T04:16:55.112Z", "published_at": "2026-09-03T12:11:42.996Z", "created_at": "2026-09-03T12:11:42.996Z", "updated_at": "2026-09-04T04:16:55.724Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_083C499BE257", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_083C499BE257/reviews", "public_url": "https://aiworkshub.io/resources/RES_083C499BE257", "distribution": { "canonical_identity": "https://github.com/majiayu000/claude-skill-registry/tree/HEAD/skills/domains/distress-screening", "syndicatable": true } }, { "id": "RES_064D8E8C707C", "resource_type": "skill", "canonical_url": "https://github.com/wsbm393/Fable-Skill", "name": "executing-hard-tasks", "summary_en": "Decompose hard tasks risk-first and verify with evidence.", "summary_zh": "将复杂任务按风险优先级分解，并以可验证的证据指导后续决策。", "description_en": "This skill guides an AI agent to decompose hard tasks by prioritizing risks and to verify progress with concrete, pasteable evidence before deciding next steps. It is designed for use within agent workflows that handle complex, multi-step objectives. The skill is distributed as a GitHub repository under the MIT license and requires no authentication or payment.", "description_zh": "该技能指导AI代理按风险优先级分解复杂任务，并使用具体、可粘贴的证据验证进展后再决定后续步骤。它适用于处理多步骤复杂目标的代理工作流。该技能以MIT许可证在GitHub上分发，无需认证或付费。", "provider_name": "wsbm393", "homepage_url": "https://github.com/wsbm393/Fable-Skill", "endpoint_url": null, "source_url": "https://github.com/wsbm393/Fable-Skill/blob/4d52fa3d8940e958ba4a915a404b1be16523e06a/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "task.decompose", "task.verify" ], "categories": [ "agent-automation", "finance-payments", "software-development" ], "industries": [ "finance" ], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "ai-translated", "license": { "spdx_id": "MIT" }, "github": { "repository": "wsbm393/Fable-Skill", "path": "SKILL.md", "commit": "4d52fa3d8940e958ba4a915a404b1be16523e06a", "stars": 25, "updated_at": "2026-07-18T18:52:41Z" }, "skill": { "content_hash": "b6a15efcbe5644799aa43f64dc230c95a25c60f02a9de2c0565795358d701d1f" }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-04T03:52:59.655Z" }, "catalog_profile": { "version": "catalog-profile-v1", "primary_category": "agent-automation", "integrations": [ "GitHub" ], "use_cases": { "en": [ "Decompose complex tasks into risk-prioritized subtasks.", "Verify progress with concrete evidence before proceeding." ], "zh": [ "将复杂任务分解为按风险排序的子任务。", "在继续之前用具体证据验证进展。" ] }, "categories": [ "agent-automation", "finance-payments", "software-development" ], "industries": [ "finance" ], "copy": { "source_language": "en", "summary_zh_state": "present", "description_zh_state": "present", "description_en_state": "present" } } }, "latest_version": "4d52fa3d8940", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-skill-reviewer", "trust": { "signal": "none", "reason": "No suspicious or malicious evidence.", "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3", "capability_definition": "partial", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "weak", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-04T03:53:00.635Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T12:10:55.873Z", "last_seen_at": "2026-09-04T03:52:59.954Z", "published_at": "2026-09-03T12:10:55.873Z", "created_at": "2026-09-03T12:10:55.873Z", "updated_at": "2026-09-04T03:53:00.635Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_064D8E8C707C", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_064D8E8C707C/reviews", "public_url": "https://aiworkshub.io/resources/RES_064D8E8C707C", "distribution": { "canonical_identity": "https://github.com/wsbm393/Fable-Skill", "syndicatable": true } }, { "id": "RES_E33C82168F24", "resource_type": "skill", "canonical_url": "https://github.com/wodeh/gstack-kimi/tree/HEAD/qa", "name": "qa", "summary_en": "Systematically QA test a web application and fix bugs found. Runs QA testing, then iteratively fixes bugs in source code, committing each fix atomically and re-verifying. Use when asked to \"qa\", \"QA\", \"test this site\", \"find bugs\", \"test and fix\", or \"fix what's broken\". Proactively suggest when the user says a feature", "summary_zh": "用于软件开发与测试与验证，支持 qa 条目描述的相关任务。", "description_en": "Systematically QA test a web application and fix bugs found. Runs QA testing, then iteratively fixes bugs in source code, committing each fix atomically and re-verifying. Use when asked to \"qa\", \"QA\", \"test this site\", \"find bugs\", \"test and fix\", or \"fix what's broken\". Proactively suggest when the user says a feature", "description_zh": "用于软件开发与测试与验证，支持 qa 条目描述的相关任务。", "provider_name": "wodeh", "homepage_url": "https://github.com/wodeh/gstack-kimi", "endpoint_url": null, "source_url": "https://github.com/wodeh/gstack-kimi/blob/5d09ea49cceb40715530fdb3c6b1ed1c61b57f5b/qa/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "software-development", "testing" ], "categories": [ "agent-skill" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "MIT" }, "github": { "repository": "wodeh/gstack-kimi", "path": "qa/SKILL.md", "stars": 0 }, "skill": { "content_hash": "eb3e98a9375f6433" }, "review_gate": { "passed": true, "policy_version": "capability-evidence-v3-luna-full", "provider": "codex", "model": "luna", "source_review_id": "eb3e98a9375f6433", "content_hash": "eb3e98a9375f6433" } }, "latest_version": "5d09ea49cceb", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-luna-batch-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3-luna-full", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "partial", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-03T13:50:06.104Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T13:50:05.310Z", "last_seen_at": "2026-09-03T13:50:05.310Z", "published_at": "2026-09-03T13:50:05.310Z", "created_at": "2026-09-03T13:50:05.310Z", "updated_at": "2026-09-03T13:50:06.104Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_E33C82168F24", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_E33C82168F24/reviews", "public_url": "https://aiworkshub.io/resources/RES_E33C82168F24", "distribution": { "canonical_identity": "https://github.com/wodeh/gstack-kimi/tree/HEAD/qa", "syndicatable": true } }, { "id": "RES_DA69365CE75A", "resource_type": "skill", "canonical_url": "https://github.com/seancrecord/scvd-general-store-repo/tree/HEAD/registry/clawhub", "name": "scvd-general-store", "summary_en": "A live x402 practice counter: real settlement, no sandbox, from $0.001. Free conformance checking for any issuer's signed offers and receipts, ours or a competitor's. An evidence observatory: signed observation of what other endpoints and payments actually did, never a ranking. Reachable six ways, including browser too", "summary_zh": "用于金融工作流与网页自动化，支持 scvd-general-store 条目描述的相关任务。", "description_en": "A live x402 practice counter: real settlement, no sandbox, from $0.001. Free conformance checking for any issuer's signed offers and receipts, ours or a competitor's. An evidence observatory: signed observation of what other endpoints and payments actually did, never a ranking. Reachable six ways, including browser too", "description_zh": "用于金融工作流与网页自动化，支持 scvd-general-store 条目描述的相关任务。", "provider_name": "seancrecord", "homepage_url": "https://github.com/seancrecord/scvd-general-store-repo", "endpoint_url": null, "source_url": "https://github.com/seancrecord/scvd-general-store-repo/blob/f08303267c8a253c55e0197114e7951535a7a6a9/registry/clawhub/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "finance", "web-automation" ], "categories": [ "agent-skill" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "MIT" }, "github": { "repository": "seancrecord/scvd-general-store-repo", "path": "registry/clawhub/SKILL.md", "stars": 3 }, "skill": { "content_hash": "c04c694da938696c" }, "review_gate": { "passed": true, "policy_version": "capability-evidence-v3-luna-full", "provider": "codex", "model": "luna", "source_review_id": "c04c694da938696c", "content_hash": "c04c694da938696c" } }, "latest_version": "f08303267c8a", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-luna-batch-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3-luna-full", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "partial", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-03T13:50:04.903Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T13:50:04.120Z", "last_seen_at": "2026-09-03T13:50:04.120Z", "published_at": "2026-09-03T13:50:04.120Z", "created_at": "2026-09-03T13:50:04.120Z", "updated_at": "2026-09-03T13:50:04.903Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_DA69365CE75A", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_DA69365CE75A/reviews", "public_url": "https://aiworkshub.io/resources/RES_DA69365CE75A", "distribution": { "canonical_identity": "https://github.com/seancrecord/scvd-general-store-repo/tree/HEAD/registry/clawhub", "syndicatable": true } }, { "id": "RES_13A087563B18", "resource_type": "skill", "canonical_url": "https://github.com/raddue/crucible/tree/HEAD/skills/temper", "name": "temper", "summary_en": "Iteratively review code changes for production readiness through fresh-eyes review loops. Use when completing tasks, implementing major features, or reviewing a change for production readiness — including when the user says \"review this PR\", \"review my changes\", \"code review\", \"check the diff\", or \"is this ready to shi", "summary_zh": "用于软件开发与项目管理，支持 temper 条目描述的相关任务。", "description_en": "Iteratively review code changes for production readiness through fresh-eyes review loops. Use when completing tasks, implementing major features, or reviewing a change for production readiness — including when the user says \"review this PR\", \"review my changes\", \"code review\", \"check the diff\", or \"is this ready to shi", "description_zh": "用于软件开发与项目管理，支持 temper 条目描述的相关任务。", "provider_name": "raddue", "homepage_url": "https://github.com/raddue/crucible", "endpoint_url": null, "source_url": "https://github.com/raddue/crucible/blob/205849b7f3636c2b0c18e6e5d8a2a0b77b970282/skills/temper/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "software-development", "project-management" ], "categories": [ "agent-skill" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "MIT" }, "github": { "repository": "raddue/crucible", "path": "skills/temper/SKILL.md", "stars": 10 }, "skill": { "content_hash": "33aa416570b84319" }, "review_gate": { "passed": true, "policy_version": "capability-evidence-v3-luna-full", "provider": "codex", "model": "luna", "source_review_id": "33aa416570b84319", "content_hash": "33aa416570b84319" } }, "latest_version": "205849b7f363", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-luna-batch-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3-luna-full", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "partial", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-03T13:50:03.641Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T13:50:02.734Z", "last_seen_at": "2026-09-03T13:50:02.734Z", "published_at": "2026-09-03T13:50:02.734Z", "created_at": "2026-09-03T13:50:02.734Z", "updated_at": "2026-09-03T13:50:03.641Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_13A087563B18", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_13A087563B18/reviews", "public_url": "https://aiworkshub.io/resources/RES_13A087563B18", "distribution": { "canonical_identity": "https://github.com/raddue/crucible/tree/HEAD/skills/temper", "syndicatable": true } }, { "id": "RES_4F767ED2B226", "resource_type": "skill", "canonical_url": "https://github.com/Eskyee/agentbot-opensource/tree/HEAD/skills/cattown", "name": "cattown", "summary_en": "Interact with Cat Town — a Farcaster-native game world on Base. Covers KIBBLE staking (stake, claim, unlock, unstake, leaderboard, deposit history); live world state (season, weather, time of day, weekend flag); fishing drops filtered by world state; Isabella's weekend fishing competition with live prize-pool math; Pau", "summary_zh": "用于模拟，支持 cattown 条目描述的相关任务。", "description_en": "Interact with Cat Town — a Farcaster-native game world on Base. 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The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.", "summary_zh": "用于设计工作流，支持 design-taste-frontend 条目描述的相关任务。", "description_en": "Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.", "description_zh": "用于设计工作流，支持 design-taste-frontend 条目描述的相关任务。", "provider_name": "NoWint", "homepage_url": "https://github.com/NoWint/BonNextMinecraftLauncher-Rust", "endpoint_url": null, "source_url": "https://github.com/NoWint/BonNextMinecraftLauncher-Rust/blob/65ab0293bc8756c8c7ac34aa2cd62e7e5407b17b/.agents/skills/design-taste-frontend/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "design" ], "categories": [ "agent-skill" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "GPL-3.0" }, "github": { "repository": "NoWint/BonNextMinecraftLauncher-Rust", "path": ".agents/skills/design-taste-frontend/SKILL.md", "stars": 18 }, "skill": { "content_hash": "ca5e266748077b2d" }, "review_gate": { "passed": true, "policy_version": "capability-evidence-v3-luna-full", "provider": "codex", "model": "luna", "source_review_id": "ca5e266748077b2d", "content_hash": "ca5e266748077b2d" } }, "latest_version": "65ab0293bc87", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-luna-batch-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3-luna-full", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "partial", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-03T13:49:52.683Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T13:49:51.783Z", "last_seen_at": "2026-09-03T13:49:51.783Z", "published_at": "2026-09-03T13:49:51.783Z", "created_at": "2026-09-03T13:49:51.783Z", "updated_at": "2026-09-03T13:49:52.683Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_25A153B41BBA", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_25A153B41BBA/reviews", "public_url": "https://aiworkshub.io/resources/RES_25A153B41BBA", "distribution": { "canonical_identity": "https://github.com/NoWint/BonNextMinecraftLauncher-Rust/tree/HEAD/.agents/skills/design-taste-frontend", "syndicatable": true } }, { "id": "RES_53AAED05A895", "resource_type": "skill", "canonical_url": "https://github.com/majiayu000/claude-skill-registry-data/tree/HEAD/testing/fastmcp", "name": "fastmcp", "summary_en": "Use this skill when building MCP (Model Context Protocol) servers with FastMCP in Python. FastMCP is a framework for creating servers that expose tools, resources, and prompts to LLMs like Claude. The skill covers server creation, tool/resource definitions, storage backends (memory/disk/Redis/DynamoDB), server lifespan", "summary_zh": "用于软件开发与数据库处理，支持 fastmcp 条目描述的相关任务。", "description_en": "Use this skill when building MCP (Model Context Protocol) servers with FastMCP in Python. FastMCP is a framework for creating servers that expose tools, resources, and prompts to LLMs like Claude. The skill covers server creation, tool/resource definitions, storage backends (memory/disk/Redis/DynamoDB), server lifespan", "description_zh": "用于软件开发与数据库处理，支持 fastmcp 条目描述的相关任务。", "provider_name": "majiayu000", "homepage_url": "https://github.com/majiayu000/claude-skill-registry-data", "endpoint_url": null, "source_url": "https://github.com/majiayu000/claude-skill-registry-data/blob/5590e2737a11b8bcb6bb3ff51683990fd489917d/testing/fastmcp/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "software-development", "database", "knowledge-management" ], "categories": [ "agent-skill" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "MIT" }, "github": { "repository": "majiayu000/claude-skill-registry-data", "path": "testing/fastmcp/SKILL.md", "stars": 18 }, "skill": { "content_hash": "476349ed9c6f7b32" }, "review_gate": { "passed": true, "policy_version": "capability-evidence-v3-luna-full", "provider": "codex", "model": "luna", "source_review_id": "476349ed9c6f7b32", "content_hash": "476349ed9c6f7b32" } }, "latest_version": "5590e2737a11", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-luna-batch-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3-luna-full", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "partial", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-03T13:49:51.381Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T13:49:50.576Z", "last_seen_at": "2026-09-03T13:49:50.576Z", "published_at": "2026-09-03T13:49:50.576Z", "created_at": "2026-09-03T13:49:50.576Z", "updated_at": "2026-09-03T13:49:51.381Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_53AAED05A895", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_53AAED05A895/reviews", "public_url": "https://aiworkshub.io/resources/RES_53AAED05A895", "distribution": { "canonical_identity": "https://github.com/majiayu000/claude-skill-registry-data/tree/HEAD/testing/fastmcp", "syndicatable": true } }, { "id": "RES_67C720AFE45C", "resource_type": "skill", "canonical_url": "https://github.com/cashwu/iphoneLocationMove/tree/HEAD/.agents/skills/cash-propose", "name": "cash-propose", "summary_en": "Create a Cash change proposal with sub-agent quality gates", "summary_zh": "用于测试与验证，支持 cash-propose 条目描述的相关任务。", "description_en": "Create a Cash change proposal with sub-agent quality gates", "description_zh": "用于测试与验证，支持 cash-propose 条目描述的相关任务。", "provider_name": "cashwu", "homepage_url": "https://github.com/cashwu/iphoneLocationMove", "endpoint_url": null, "source_url": "https://github.com/cashwu/iphoneLocationMove/blob/c62dd5cdbe879bf72bc04878d4a12957a11e39c6/.agents/skills/cash-propose/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "testing" ], "categories": [ "agent-skill" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "MIT" }, "github": { "repository": "cashwu/iphoneLocationMove", "path": ".agents/skills/cash-propose/SKILL.md", "stars": 62 }, "skill": { "content_hash": "da7e586357084d58" }, "review_gate": { "passed": true, "policy_version": "capability-evidence-v3-luna-full", "provider": "codex", "model": "luna", "source_review_id": "da7e586357084d58", "content_hash": 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"https://aiworkshub.io/api/v1/resources/RES_67C720AFE45C/reviews", "public_url": "https://aiworkshub.io/resources/RES_67C720AFE45C", "distribution": { "canonical_identity": "https://github.com/cashwu/iphoneLocationMove/tree/HEAD/.agents/skills/cash-propose", "syndicatable": true } }, { "id": "RES_E26A00AA9641", "resource_type": "skill", "canonical_url": "https://github.com/majiayu000/claude-skill-registry/tree/HEAD/skills/design/wordpress-magic-seo-frontend-2026-meastt-wordpressmagicseo", "name": "wordpress-magic-seo-frontend-2026", "summary_en": "Create cutting-edge WordPress plugin admin interfaces using 2026 design trends for AI-powered SEO tools. Use this skill when building WordPress admin dashboards, settings pages, or React-based plugin UIs. Implements fluid organic layouts, glassmorphism effects, Transformative Teal color theory, micro-delight interactio", "summary_zh": "用于软件开发与营销工作流，支持 wordpress-magic-seo-frontend-2026 条目描述的相关任务。", "description_en": "Create cutting-edge WordPress plugin admin interfaces using 2026 design trends for AI-powered SEO tools. Use this skill when building WordPress admin dashboards, settings pages, or React-based plugin UIs. Implements fluid organic layouts, glassmorphism effects, Transformative Teal color theory, micro-delight interactio", "description_zh": "用于软件开发与营销工作流，支持 wordpress-magic-seo-frontend-2026 条目描述的相关任务。", "provider_name": "majiayu000", "homepage_url": "https://github.com/majiayu000/claude-skill-registry", "endpoint_url": null, "source_url": "https://github.com/majiayu000/claude-skill-registry/blob/8929dcba0964653ab807d28d1c1df10eb706f7d2/skills/design/wordpress-magic-seo-frontend-2026-meastt-wordpressmagicseo/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "software-development", "marketing", "data-analysis" ], "categories": [ "agent-skill" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "MIT" }, "github": { "repository": "majiayu000/claude-skill-registry", "path": "skills/design/wordpress-magic-seo-frontend-2026-meastt-wordpressmagicseo/SKILL.md", "stars": 590 }, "skill": { "content_hash": "a2556b1b49a1224a" }, "review_gate": { "passed": true, "policy_version": "capability-evidence-v3-luna-full", "provider": "codex", "model": "luna", "source_review_id": "a2556b1b49a1224a", "content_hash": "a2556b1b49a1224a" } }, "latest_version": "8929dcba0964", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-luna-batch-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3-luna-full", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "partial", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-03T13:49:48.637Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T13:49:47.713Z", "last_seen_at": "2026-09-03T13:49:47.713Z", "published_at": "2026-09-03T13:49:47.713Z", "created_at": "2026-09-03T13:49:47.713Z", "updated_at": "2026-09-03T13:49:48.637Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_E26A00AA9641", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_E26A00AA9641/reviews", "public_url": "https://aiworkshub.io/resources/RES_E26A00AA9641", "distribution": { "canonical_identity": "https://github.com/majiayu000/claude-skill-registry/tree/HEAD/skills/design/wordpress-magic-seo-frontend-2026-meastt-wordpressmagicseo", "syndicatable": true } }, { "id": "RES_1546D72CB977", "resource_type": "skill", "canonical_url": "https://github.com/zeroes-ones/Skills/tree/HEAD/skills/06-quality/code-simplification", "name": "code-simplification", "summary_en": "Use when reducing code complexity while preserving exact behavior, refactoring legacy code, eliminating dead code, flattening deep nesting, simplifying conditionals, removing premature abstractions, or applying Chesterton's Fence before removing any code. Handles complexity scoring (cyclomatic, cognitive), language-spe", "summary_zh": "用于软件开发，支持 code-simplification 条目描述的相关任务。", "description_en": "Use when reducing code complexity while preserving exact behavior, refactoring legacy code, eliminating dead code, flattening deep nesting, simplifying conditionals, removing premature abstractions, or applying Chesterton's Fence before removing any code. Handles complexity scoring (cyclomatic, cognitive), language-spe", "description_zh": "用于软件开发，支持 code-simplification 条目描述的相关任务。", "provider_name": "zeroes-ones", "homepage_url": "https://github.com/zeroes-ones/Skills", "endpoint_url": null, "source_url": "https://github.com/zeroes-ones/Skills/blob/0d80cc53a1c3f3defc13586368a1fce047a4ed0d/skills/06-quality/code-simplification/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "software-development" ], "categories": [ "agent-skill" ], "industries": [], "protocols": [ "agent-skills" ], "auth": { "type": "none", "required": false }, "pricing": { "model": "free" }, "input_schema": {}, "output_schema": {}, "metadata": { "content_language": "en", "translation_status": "luna-reviewed", "license": { "spdx_id": "MIT" }, "github": { "repository": "zeroes-ones/Skills", "path": "skills/06-quality/code-simplification/SKILL.md", "stars": 1 }, "skill": { "content_hash": "53d87390da0de5f7" }, "review_gate": { "passed": true, "policy_version": "capability-evidence-v3-luna-full", "provider": "codex", "model": "luna", "source_review_id": "53d87390da0de5f7", "content_hash": "53d87390da0de5f7" } }, "latest_version": "0d80cc53a1c3", "status": "listed", "health_status": "unknown", "source_kind": "imported", "source_agent": "aiworkshub-luna-batch-reviewer", "trust": { "signal": "none", "reason": null, "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v3-luna-full", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "partial", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": "2026-09-03T13:49:47.221Z" }, "experience_count": 0, "verified_experience_count": 0, "usage_count": 0, "success_rate": null, "first_seen_at": "2026-09-03T13:49:46.285Z", "last_seen_at": "2026-09-03T13:49:46.285Z", "published_at": "2026-09-03T13:49:46.285Z", "created_at": "2026-09-03T13:49:46.285Z", "updated_at": "2026-09-03T13:49:47.221Z", "api_url": "https://aiworkshub.io/api/v1/resources/RES_1546D72CB977", "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_1546D72CB977/reviews", "public_url": "https://aiworkshub.io/resources/RES_1546D72CB977", "distribution": { "canonical_identity": "https://github.com/zeroes-ones/Skills/tree/HEAD/skills/06-quality/code-simplification", "syndicatable": true } }, { "id": "RES_8D7BF1D6C7BD", "resource_type": "skill", "canonical_url": "https://github.com/a23882/instant-transmutation/tree/HEAD/skills/%E5%AE%A1%E8%AE%A1%E5%9F%BA%E7%A1%80%E6%96%B9%E6%B3%95%E7%B1%BB/%E5%8F%82%E6%95%B0%E5%8F%AF%E6%8E%A7%E6%80%A7%E5%88%A4%E6%96%AD", "name": "parameter-controllability-analysis", "summary_en": "Use when deciding whether a parameter, object field, stored value, claim, file name, URL, path, expression, selector, or object id remains attacker-controlled at a sensitive operation, especially when the result may be written into a report and must be bounded by the official security model, scope, and expected behavio", "summary_zh": "用于安全审计与数据分析，支持 parameter-controllability-analysis 条目描述的相关任务。", "description_en": "Use when deciding whether a parameter, object field, stored value, claim, file name, URL, path, expression, selector, or object id remains attacker-controlled at a sensitive operation, especially when the result may be written into a report and must be bounded by the official security model, scope, and expected behavio", "description_zh": "用于安全审计与数据分析，支持 parameter-controllability-analysis 条目描述的相关任务。", "provider_name": "a23882", "homepage_url": "https://github.com/a23882/instant-transmutation", "endpoint_url": null, "source_url": "https://github.com/a23882/instant-transmutation/blob/b0a38d182f7d58920b356c98a2a35f20f1732075/skills/%E5%AE%A1%E8%AE%A1%E5%9F%BA%E7%A1%80%E6%96%B9%E6%B3%95%E7%B1%BB/%E5%8F%82%E6%95%B0%E5%8F%AF%E6%8E%A7%E6%80%A7%E5%88%A4%E6%96%AD/SKILL.md", "icon_url": null, 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