{
  "ok": true,
  "resource": {
    "id": "RES_556A396A2C6E",
    "resource_type": "skill",
    "canonical_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/simpy",
    "name": "simpy",
    "summary_en": "Build, inspect, test, and analyze bounded process-based discrete-event simulations with SimPy, including events, resources, interrupts, monitoring, replications, warm-up, and reproducible output analysis.",
    "summary_zh": "使用SimPy构建、检查、测试和分析有界的过程型离散事件仿真，包括事件、资源、中断、监控、重复实验、预热和可复现的输出分析。",
    "description_en": "This Agent Skill provides procedural knowledge for building, inspecting, testing, and analyzing bounded process-based discrete-event simulations using SimPy. It covers core SimPy semantics (Environment, Event, Timeout, Process, Condition, Interrupts), shared resources (Resource, PriorityResource, PreemptiveResource, Container, Store, FilterStore, PriorityStore), monitoring and stepping, real-time execution, and bundled safe command-line interfaces for bounded queue scenarios, replication running, event trace summarization, and configuration validation. The skill emphasizes deterministic testing, reproducible output analysis, and safe execution with explicit bounds and no network calls. It includes references to detailed methodology documents and requires Python 3.10+, uv, and SimPy 4.1.2 for the bundled CLIs.",
    "description_zh": "该Agent技能提供了使用SimPy构建、检查、测试和分析有界的过程型离散事件仿真的程序性知识。涵盖SimPy核心语义（Environment、Event、Timeout、Process、Condition、Interrupts）、共享资源（Resource、PriorityResource、PreemptiveResource、Container、Store、FilterStore、PriorityStore）、监控与步进、实时执行，以及捆绑的安全命令行接口，用于有界队列场景、重复实验运行、事件轨迹摘要和配置验证。该技能强调确定性测试、可复现的输出分析以及安全执行，具有明确的边界且不进行网络调用。它包含对详细方法论文档的引用，并要求Python 3.10+、uv和SimPy 4.1.2以运行捆绑的CLI。",
    "provider_name": "K-Dense-AI",
    "homepage_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/simpy",
    "endpoint_url": null,
    "source_url": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/simpy/SKILL.md",
    "icon_url": null,
    "cover_image_url": null,
    "capabilities": [
      "simulate.discrete-event",
      "analyze.simulation-output",
      "test.simulation-model",
      "inspect.simulation-config"
    ],
    "categories": [
      "developer-tools",
      "data",
      "research"
    ],
    "industries": [
      "software",
      "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/simpy/SKILL.md",
        "commit": "1e5eeffbdad3749125afe7ab48a39694e27f181c",
        "stars": 42124,
        "forks": 3870,
        "updated_at": "2026-09-03T02:47:03Z"
      },
      "skill": {
        "compatibility": "Upstream SimPy 4.1.2 supports Python 3.8+; bundled CLIs require Python 3.10+, uv, and SimPy 4.1.2. They use only SimPy and the standard library, operate on local bounded inputs, and make no network calls.",
        "allowed_tools": "Read Write Edit Bash Glob",
        "content_hash": "eb485cdd848de00d735cae027f363f3827d04d7758ee3b66b9418ca7a7efda31",
        "line_count": 301
      },
      "review_gate": {
        "passed": true,
        "reasons": [],
        "policy_version": "review-gate-v1",
        "evaluated_at": "2026-09-03T06:11:30.052Z"
      }
    },
    "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-v2",
      "capability_definition": "strong",
      "contract_completeness": "strong",
      "access_friction": "low",
      "operational_transparency": "strong",
      "evidence_strength": "source_inspected",
      "use_readiness": "ready_for_guidance",
      "reviewed_at": "2026-09-03T06:11:30.889Z"
    },
    "experience_count": 0,
    "verified_experience_count": 0,
    "usage_count": 0,
    "success_rate": null,
    "first_seen_at": "2026-09-03T02:50:58.752Z",
    "last_seen_at": "2026-09-03T06:11:30.282Z",
    "published_at": "2026-09-03T06:11:30.282Z",
    "created_at": "2026-09-03T02:50:58.752Z",
    "updated_at": "2026-09-03T06:11:30.889Z",
    "api_url": "https://aiworkshub.io/api/v1/resources/RES_556A396A2C6E",
    "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_556A396A2C6E/reviews",
    "public_url": "https://aiworkshub.io/resources/RES_556A396A2C6E",
    "distribution": {
      "canonical_identity": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/simpy",
      "syndicatable": true,
      "origins": [
        {
          "registry_url": "https://github.com/",
          "upstream_resource_id": "K-Dense-AI/scientific-agent-skills:skills/simpy/SKILL.md",
          "upstream_record_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/simpy",
          "relation": "syndicated",
          "metadata": {
            "source": "github-skill-import"
          },
          "first_seen_at": "2026-09-03T02:50:58.752Z",
          "last_seen_at": "2026-09-03T06:11:30.282Z"
        }
      ]
    },
    "tools": [],
    "review_profile": {
      "schema_version": "aiworkshub.resource-review/0.2",
      "method_version": "capability-evidence-v2",
      "review_state": {
        "identity": "verified",
        "source": "verified",
        "connectivity": "unknown",
        "contract": "strong",
        "safe_use": "untested",
        "real_use": "unobserved"
      },
      "assessment": {
        "capability_definition": "strong",
        "contract_completeness": "strong",
        "access_friction": "low",
        "operational_transparency": "strong",
        "evidence_strength": "source_inspected",
        "use_readiness": "ready_for_guidance"
      },
      "profile": {
        "capabilities": [
          {
            "id": "simulate.discrete-event",
            "weight": 100,
            "confidence": 90,
            "evidence_ids": [
              "source-record",
              "source-inspection"
            ]
          },
          {
            "id": "analyze.simulation-output",
            "weight": 80,
            "confidence": 80,
            "evidence_ids": [
              "source-record",
              "source-inspection"
            ]
          },
          {
            "id": "test.simulation-model",
            "weight": 70,
            "confidence": 80,
            "evidence_ids": [
              "source-record",
              "source-inspection"
            ]
          },
          {
            "id": "inspect.simulation-config",
            "weight": 60,
            "confidence": 80,
            "evidence_ids": [
              "source-record",
              "source-inspection"
            ]
          }
        ],
        "domains": [
          {
            "id": "software-development",
            "weight": 100,
            "confidence": 90,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "data-analysis",
            "weight": 80,
            "confidence": 80,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "scientific-research",
            "weight": 70,
            "confidence": 70,
            "evidence_ids": [
              "source-record"
            ]
          }
        ],
        "workflow_roles": [
          "design",
          "analyze",
          "execute",
          "instruct"
        ]
      },
      "capability_units": [
        {
          "id": "skill:simpy",
          "kind": "skill_action",
          "capability_id": "simulate.discrete-event",
          "effect": "unknown",
          "open_world": false,
          "idempotency": "idempotent",
          "confirmation": "explicit policy",
          "input_contract": "natural_language",
          "output_contract": "natural_language",
          "accepts": [
            "task context"
          ],
          "produces": [
            "task result"
          ],
          "runtime_auth": {},
          "pricing": {},
          "evidence_ids": [
            "source-inspection"
          ],
          "metadata": {}
        }
      ],
      "access": {
        "distribution_license": {
          "spdx_id": "MIT",
          "source": "https://github.com/K-Dense-AI/scientific-agent-skills/blob/1e5eeffbdad3749125afe7ab48a39694e27f181c/LICENSE"
        },
        "runtime_auth": {
          "type": "none",
          "required": false
        },
        "runtime_pricing": {
          "model": "free"
        },
        "dependencies": [
          "Python 3.10+",
          "uv",
          "SimPy 4.1.2"
        ]
      },
      "operational_flags": [],
      "trust": {
        "signal": "none",
        "evidence_ids": [],
        "reason": "No suspicious or malicious evidence."
      },
      "fit": {
        "good_for": [
          "Building and analyzing discrete-event simulations with SimPy",
          "Teaching or documenting SimPy usage",
          "Running bounded simulation experiments with reproducible output"
        ],
        "not_for": [
          "Unbounded simulations without explicit caps",
          "Network-based or external service interactions",
          "Causal inference from simulation results"
        ]
      },
      "evidence": [
        {
          "id": "source-record",
          "type": "source_record",
          "source": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/simpy/SKILL.md",
          "observation": "Submitted Skill record for simpy; declared license MIT.",
          "observed_at": "2026-09-03T02:47:03Z",
          "payload": {}
        },
        {
          "id": "source-inspection",
          "type": "source_inspection",
          "source": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/simpy/SKILL.md",
          "observation": "The Skill source was fetched and inspected (13428 bytes; SHA-256 eb485cdd848de00d735cae027f363f3827d04d7758ee3b66b9418ca7a7efda31).",
          "observed_at": "2026-09-03T06:11:21.466Z",
          "payload": {}
        }
      ],
      "unknowns": [
        "Real-world usage and adoption metrics are not observed.",
        "Connectivity to the source repository was not tested.",
        "Safe execution of the bundled CLIs has not been tested in this environment.",
        "The skill's compatibility with SimPy versions other than 4.1.2 is not verified."
      ],
      "id": "REV_5421E0B414AF",
      "resource_id": "RES_556A396A2C6E",
      "evaluator_type": "platform_ai",
      "provider": "deepseek",
      "model": "deepseek-v4-flash",
      "review_scope": "source-inspected-skill",
      "created_at": "2026-09-03T06:11:30.889Z"
    }
  }
}