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Agent Skill · 研究检索

skill-system-graph(技能系统图)

skill-system-graph 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

skill-system-graph 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为可写文件;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 51,696。

总安装 576周安装 24GitHub Stars 4下载 192核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:skill-system-graph(技能系统图)
来源仓库:https://github.com/arthur0824hao/skills
仓库路径:skills/skill-system-graph
安装命令:
npx skills add https://github.com/arthur0824hao/skills --skill skill-system-graph
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/arthur0824hao/skills --skill skill-system-graph

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。支持基于关键词、任务场景或来源线索进行信息筛选与整理。通过 npx skills add 命令从指定 GitHub 仓库安装使用。安装前需确认权限范围、维护状态及是否触发联网或文件操作。

skill-system-graph 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/skill-system-graph

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/arthur0824hao/skills --skill skill-system-grap…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要可写文件,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

skill-system-graph 怎么安装?

在终端执行 npx skills add https://github.com/arthur0824hao/skills --skill skill-system-graph。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

skill-system-graph 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

skill-system-graph 需要什么权限?

权限级别是可写文件。该 Skill 可能写入或修改本地文件,使用前需要确认目标目录和修改范围。

skill-system-graph 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

skill-system-graph 用的人多吗?

公开数据是累计安装 576 次,近一周安装 24 次,下载 192 次,GitHub 4 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

skill-system-graph 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
skill-system-graph

技能系统图 · 本页

5764可写文件未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Skill System Graph

skill-system-graph is an AI-first navigation layer for project dependencies. It reads skill specs and v2 behavior specs, preserves declared relationship types, and syncs that graph into PostgreSQL for queryable navigation and dependency health checks.

This skill is SKILL.spec.yaml-first. It does not read SKILL.behavior.yaml for canonical graph construction.

Purpose

  • Answer dependency questions quickly: what depends on what, and what changes may cascade.
  • Provide CLI primitives where show reads the current spec-scan model and neighbors/path/impact query persisted edges.
  • Keep behavior discovery fast via incremental refresh using source hashes.

Output Contract

Agents should run with --format json by default for stable automation.

  • json output: machine-readable object, one record per command.
  • text output: human-readable fallback only.

Core Operations

skill-system-graph exposes graph subcommands in scripts/.

graph show

Display all known nodes and edges from the current spec-scan model.

python3 "$(pwd)/skills/skill-system-graph/scripts/graph_cli.py" show [--skills-dir skills] [--check-deps] [--format json|text]

JSON shape (agent-facing):

{
  "status": "ok",
  "nodes": [{"skill_name": "...", "description": "...", "spec_path": "...", "operations_count": 0, "content_hash": "...", "stub": false}],
  "edges": [{"source": "...", "target": "...", "edge_type": "depends_on|delegates_to|reads|writes|..."}],
  "node_count": 0,
  "edge_count": 0
}

When --check-deps is used, the payload also includes dependency_report with missing and conflicting dependency diagnostics plus suggested fixes.

graph neighbors <skill_name>

List incoming and outgoing direct neighbors for a specific skill.

python3 "$(pwd)/skills/skill-system-graph/scripts/graph_cli.py" neighbors skill-system-router [--format json|text]

JSON shape:

{
  "skill": "skill-system-router",
  "outgoing": [{"skill_name": "skill-system-postgres", "edge_type": "depends_on"}],
  "incoming": [{"skill_name": "skill-system-tkt", "edge_type": "delegates_to"}],
  "status": "ok"
}

graph path <from_skill> <to_skill>

Find the shortest dependency path between two skills.

python3 "$(pwd)/skills/skill-system-graph/scripts/graph_cli.py" path skill-system-memory skill-system-postgres [--max-depth 10] [--format json|text]

JSON shape:

{
  "from_skill": "skill-system-memory",
  "to_skill": "skill-system-postgres",
  "path": ["skill-system-memory", "skill-system-router", "skill-system-postgres"],
  "found": true,
  "max_depth": 10
}

graph impact <skill_name>

Return transitive dependents (all skills that (transitively) depend on the given one).

python3 "$(pwd)/skills/skill-system-graph/scripts/graph_cli.py" impact skill-system-postgres [--max-depth 10] [--format json|text]

JSON shape:

{
  "skill": "skill-system-postgres",
  "impact": [
    {"impact_skill": "skill-system-memory", "depth": 1, "path": ["skill-system-memory", "skill-system-postgres"]},
    {"impact_skill": "skill-system-gui", "depth": 2, "path": ["skill-system-gui", "skill-system-memory", "skill-system-postgres"]}
  ],
  "impact_count": 2,
  "max_depth": 10,
  "status": "ok"
}

graph refresh

Rebuild and sync the graph from discovered specs in one command.

python3 "$(pwd)/skills/skill-system-graph/scripts/graph_cli.py" refresh [--skills-dir skills] [--force] [--format json|text]

JSON shape:

{
  "status": "ok",
  "parsed": 12,
  "inserted": 12,
  "updated": 0,
  "skipped": 0,
  "removed": 0
}

If refresh detects a dependency cycle, it fails closed and returns the full cycle path.

Internal helper operations

  • parse-specs: scans SKILL.spec.yaml, builds canonical graph model, returns parse summary.
  • sync-graph: persists graph model into PostgreSQL with hash-aware upserts.

The orchestrator (skill-system-router) is expected to use these primitives to keep data fresh before calls that require persistence guarantees.

Dependency Direction and Effect

This skill delegates to no further skill for execution (delegates_to: []) and depends on:

  • skill-system-postgres for persisted graph storage
  • skill-system-behavior for spec schema and behavior tooling context

Notes for AI Use

  • Prefer --format json in automation scripts.
  • Use text mode for quick operator inspection during debugging.
  • Treat graph refresh as the authoritative source update step before long-running dependency calculations.
{
  "schema_version": "2.0",
  "id": "skill-system-graph",
  "version": "0.1.0",
  "capabilities": ["graph-navigation", "behavior-query", "dependency-analysis"],
  "effects": ["fs.read", "db.read", "db.write"],
  "operations": {
    "parse-specs": {
      "description": "Parse all skill SKILL.spec.yaml files into a normalized graph model.",
      "input": {
        "skills_dir": {"type": "string", "required": false, "description": "Root directory that contains skills/"},
        "include_invalid": {"type": "boolean", "required": false, "description": "Include malformed spec metadata in the parse report"}
      },
      "output": {
        "description": "Normalized graph model plus parse report.",
        "fields": {"graph": "object", "parse_report": "object"}
      },
      "entrypoints": {
        "agent": "Use scripts/graph_core.py parse helpers to scan SKILL.spec.yaml files only"
      }
    },
    "sync-graph": {
      "description": "Sync the normalized graph model into PostgreSQL graph tables.",
      "input": {
        "skills_dir": {"type": "string", "required": false, "description": "Root directory that contains skills/"},
        "force": {"type": "boolean", "required": false, "description": "Force rebuild ignoring cached hashes"}
      },
      "output": {
        "description": "Inserted, updated, skipped, and removed counters.",
        "fields": {"sync_result": "object"}
      },
      "entrypoints": {
        "agent": "Use scripts/graph_core.py sync helpers to upsert graph state into PostgreSQL"
      }
    },
    "show": {
      "description": "Display the full skill graph from the current spec-scan graph model.",
      "input": {
        "skills_dir": {"type": "string", "required": false, "description": "Root directory that contains skills/"},
        "format": {"type": "string", "required": false, "description": "Output format: json or text"},
        "check_deps": {"type": "boolean", "required": false, "description": "Include missing/conflicting dependency diagnostics"}
      },
      "output": {
        "description": "Full graph view with nodes and edges.",
        "fields": {"graph_view": "object"}
      },
      "entrypoints": {
        "unix": ["python3", "{skill_dir}/scripts/graph_cli.py", "show"],
        "windows": ["python", "{skill_dir}/scripts/graph_cli.py", "show"]
      }
    },
    "neighbors": {
      "description": "List direct neighbor skills for a target skill.",
      "input": {
        "skill_name": {"type": "string", "required": true, "description": "Skill id to inspect"},
        "format": {"type": "string", "required": false, "description": "Output format: json or text"}
      },
      "output": {
        "description": "Outgoing and incoming neighbors with edge types.",
        "fields": {"neighbors": "object"}
      },
      "entrypoints": {
        "unix": ["python3", "{skill_dir}/scripts/graph_cli.py", "neighbors", "{skill_name}"],
        "windows": ["python", "{skill_dir}/scripts/graph_cli.py", "neighbors", "{skill_name}"]
      }
    },
    "path": {
      "description": "Find the shortest dependency path between two skills.",
      "input": {
        "from_skill": {"type": "string", "required": true, "description": "Source skill id"},
        "to_skill": {"type": "string", "required": true, "description": "Destination skill id"},
        "max_depth": {"type": "number", "required": false, "description": "Traversal depth guard"},
        "format": {"type": "string", "required": false, "description": "Output format: json or text"}
      },
      "output": {
        "description": "Shortest path list and found flag.",
        "fields": {"path_result": "object"}
      },
      "entrypoints": {
        "unix": ["python3", "{skill_dir}/scripts/graph_cli.py", "path", "{from_skill}", "{to_skill}"],
        "windows": ["python", "{skill_dir}/scripts/graph_cli.py", "path", "{from_skill}", "{to_skill}"]
      }
    },
    "impact": {
      "description": "Find all transitive dependents for one skill.",
      "input": {
        "skill_name": {"type": "string", "required": true, "description": "Skill id whose dependents are requested"},
        "max_depth": {"type": "number", "required": false, "description": "Traversal depth guard"},
        "format": {"type": "string", "required": false, "description": "Output format: json or text"}
      },
      "output": {
        "description": "Transitive dependents with count plus depth/path metadata.",
        "fields": {"impact_result": "object"}
      },
      "entrypoints": {
        "unix": ["python3", "{skill_dir}/scripts/graph_cli.py", "impact", "{skill_name}"],
        "windows": ["python", "{skill_dir}/scripts/graph_cli.py", "impact", "{skill_name}"]
      }
    },
    "refresh": {
      "description": "Rebuild graph from specs and refresh persistence in one command.",
      "input": {
        "skills_dir": {"type": "string", "required": false, "description": "Root directory that contains skills/"},
        "force": {"type": "boolean", "required": false, "description": "Force rebuild ignoring cached hashes"},
        "format": {"type": "string", "required": false, "description": "Output format: json or text"}
      },
      "output": {
        "description": "Parsed spec count plus sync counters.",
        "fields": {"refresh_result": "object"}
      },
      "entrypoints": {
        "unix": ["python3", "{skill_dir}/scripts/graph_cli.py", "refresh"],
        "windows": ["python", "{skill_dir}/scripts/graph_cli.py", "refresh"]
      }
    }
  },
  "stdout_contract": {
    "last_line_json": true,
    "note": "CLI commands support stable JSON output for automation. Internal helper operations are agent-executed."
  }
}

平台分布

Codex

39.15%
按下载量换算75

Claude

29.29%
按下载量换算56

Cursor

19.22%
按下载量换算37

Gemini CLI

9.24%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

可写文件

该 Skill 可能写入或修改本地文件,使用前需要确认目标目录和修改范围。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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