{ "ok": true, "resource": { "id": "RES_64336C6EB8A4", "resource_type": "skill", "canonical_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/scikit-bio", "name": "scikit-bio", "summary_en": "Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.", "summary_zh": "生物数据工具包。用于微生物组分析的序列分析、比对、系统发育树、多样性指标（alpha/beta、UniFrac）、排序（PCoA）、PERMANOVA、FASTA/Newick 输入输出。", "description_en": "This Agent Skill provides procedural knowledge for using the scikit-bio Python library in bioinformatics analyses. Based on the inspected SKILL.md source, it covers sequence manipulation (DNA/RNA/Protein, FASTA/FASTQ/GenBank I/O), pairwise and multiple sequence alignment (pair_align engine), phylogenetic tree construction and analysis (NJ, UPGMA, GME, BME, Newick I/O), alpha/beta diversity metrics (including Faith's PD and UniFrac), ordination methods (PCoA, CA, CCA, RDA), statistical tests (PERMANOVA, ANOSIM, Mantel, differential abundance), file I/O for 19+ biological formats, distance matrix handling, biological tables (BIOM, pandas/polars/AnnData dispatch), and protein embeddings. The skill declares compatibility with Python 3.10+, scikit-bio 0.7+, and NumPy 2.0+, and allows Read, Write, Edit, and Bash tools. The source record declares an MIT license, but the inspected SKILL.md frontmatter states BSD-3-Clause; this discrepancy is noted.", "description_zh": "该Agent技能提供了在生物信息学分析中使用scikit-bio Python库的程序性知识。根据检查的SKILL.md源文件，它涵盖序列操作（DNA/RNA/蛋白质，FASTA/FASTQ/GenBank输入输出）、成对和多序列比对（pair_align引擎）、系统发育树的构建与分析（NJ、UPGMA、GME、BME、Newick输入输出）、alpha/beta多样性指标（包括Faith's PD和UniFrac）、排序方法（PCoA、CA、CCA、RDA）、统计检验（PERMANOVA、ANOSIM、Mantel、差异丰度）、19种以上生物格式的文件输入输出、距离矩阵处理、生物表格（BIOM、pandas/polars/AnnData调度）以及蛋白质嵌入。该技能声明兼容Python 3.10+、scikit-bio 0.7+和NumPy 2.0+，并允许读取、写入、编辑和Bash工具。源记录声明MIT许可证，但检查的SKILL.md前置元数据声明BSD-3-Clause；此差异已记录。", "provider_name": "K-Dense-AI", "homepage_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/scikit-bio", "endpoint_url": null, "source_url": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/scikit-bio/SKILL.md", "icon_url": null, "cover_image_url": null, "capabilities": [ "bioinformatics.sequence-analysis", "bioinformatics.alignment", "bioinformatics.phylogenetics", "bioinformatics.diversity-analysis", "bioinformatics.ordination", "bioinformatics.statistical-testing", "bioinformatics.file-io", "bioinformatics.distance-matrices", "bioinformatics.biological-tables", "bioinformatics.protein-embeddings" ], "categories": [ "research", "data" ], "industries": [ "health", "general" ], "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/scikit-bio/SKILL.md", "commit": "1e5eeffbdad3749125afe7ab48a39694e27f181c", "stars": 42124, "forks": 3870, "updated_at": "2026-09-03T02:47:03Z" }, "skill": { "compatibility": "Requires Python 3.10+ and scikit-bio 0.7+ (uv pip install scikit-bio). NumPy 2.0+ is required. Optional matplotlib/seaborn/plotly for plotting; biom-format for BIOM tables; polars/anndata for table interoperability.", "allowed_tools": "Read Write Edit Bash", "content_hash": "bc9a14071535e0e492476ea196be985b164a372be00189ad11a1083a55b27743", "line_count": 487 }, "review_gate": { "passed": true, "reasons": [], "policy_version": "review-gate-v1", "evaluated_at": "2026-09-03T06:10:29.464Z" } }, "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 found.", "signals": { "yellow": 0, "red": 0 } }, "review_summary": { "method_version": "capability-evidence-v2", "capability_definition": "strong", "contract_completeness": "natural_language", "access_friction": "low", "operational_transparency": "partial", "evidence_strength": "source_inspected", "use_readiness": "guided_use", "reviewed_at": 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