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Agent Skill · 研究检索

skill-chain(技能链)

skill-chain 用于查找、检索和筛选相关信息,适合在 OpenClaw 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-chain 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为操作浏览器;许可证为 MIT-0,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 16,205。

总安装 7,320周安装 305GitHub Stars 2下载 2,440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
MIT-0
版本
1.0.1

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-chain(技能链)
来源仓库:https://github.com/hyx-cn/skill-chain
安装命令:
openclaw skills install skill-chain
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install skill-chain

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。

skill-chain 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词快速定位候选结果时使用。适用于分析 OpenClaw 技能生态系统,了解工具和包依赖关系。可发现技能冲突和供应链风险,优化本地技能配置。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。

适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

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 OpenClaw;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 openclaw skills install skill-chain;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

    它需要操作浏览器,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-chain 怎么安装?

在终端执行 openclaw skills install skill-chain。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

skill-chain 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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-chain 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

skill-chain 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

skill-chain 用的人多吗?

公开数据是累计安装 7,320 次,近一周安装 305 次,下载 2,440 次,GitHub 2 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-chain 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 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

  • 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 OpenClaw,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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-chain

技能链 · 本页

7,3202操作浏览器MIT-0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

name
skill-chain
description
Supply chain intelligence for OpenClaw skills. Use when analyzing the local skill ecosystem, understanding tool and package dependencies, discovering skill categories, mapping relationships between skills, checking security posture, auditing skill health, detecting overlaps, or generating an ecosystem health report. Trigger on "analyze my skills", "skill supply chain", "what tools do my skills use", "skill dependencies", "skill inventory", "ecosystem report", "which skills use X package", "skill categories", "popular skills", "skill security", "skill health", "skill completeness", "overlapping skills".

SkillChain

Supply chain intelligence and ecosystem analysis for OpenClaw skills. Operates offline-first against locally installed skills; optionally enriches with live clawhub metadata (stars, downloads, moderation verdicts) when network is available.

When to Use

TriggerAction
"Analyze my skills" / "skill inventory"ingest analyze-all (one-shot)
"What tools / packages do my skills use?"analyze packages
"Show dependencies for skill X"analyze supply-chain --skill <slug>
"Which skills share package X?"analyze find-users --package <name>
"Skill categories / ecosystem breakdown"analyze categories
"How complete / healthy are my skills?"analyze health
"Do any skills overlap or duplicate?"analyze overlaps
"Sync online popularity / security data"ingest enrich
"Full ecosystem report with insights"analyze report
"Rebuild graph from scratch"ingest reset && ingest scan

Workflow

One-shot (recommended)

# Reset, scan, health check, overlap analysis, full report — all in one command
python3 scripts/ingest.py analyze-all

# With custom directories
python3 scripts/ingest.py analyze-all --dirs ~/.cursor/skills-cursor ~/.openclaw/skills ~/Downloads/skills-main/skills

Step 1 — Ingest (build the graph from local skills)

# Auto-discover skills under default paths
python3 scripts/ingest.py scan

# Specify directories explicitly
python3 scripts/ingest.py scan --dirs ~/Downloads/skills-main/skills ~/.codex/skills ~/Downloads/ontology

# Online enrichment: adds stars, downloads, moderation verdict from clawhub
# Skipped automatically if network is unavailable
python3 scripts/ingest.py enrich

# Check what's currently in the graph
python3 scripts/ingest.py status

# Reset and rebuild
python3 scripts/ingest.py reset
python3 scripts/ingest.py scan

Step 2 — Analyze

# Ecosystem overview (counts, categories, top packages)
python3 scripts/analyze.py stats

# Category distribution
python3 scripts/analyze.py categories

# Skill completeness health scores (0-100 per skill, with specific issues)
python3 scripts/analyze.py health

# Detect overlapping or complementary skill pairs
python3 scripts/analyze.py overlaps

# Top N skills by a metric
python3 scripts/analyze.py top --by stars --limit 10
python3 scripts/analyze.py top --by downloads --limit 10

# Skill profile card (dependencies, tools, bins, invocation pattern, online metrics)
python3 scripts/analyze.py profile --skill ontology

# Full supply chain for a skill (invoked_via → requires_bin → tools → packages → skill deps)
python3 scripts/analyze.py supply-chain --skill agent-browser

# Find all skills that use a specific package
python3 scripts/analyze.py find-users --package playwright

# Most-used packages across all skills
python3 scripts/analyze.py packages --top 20

# Full markdown report with Key Insights section
python3 scripts/analyze.py report

Data Sources

SourceWhat it providesRequired?
SKILL.md frontmattername, description, license, allowed-tools, metadata.requires.bins, read_whenYes
requirements.txtDeclared Python package deps (pypi)When present
pyproject.tomlPython deps: PEP 621, Poetry, optional-depsWhen present
PipfilePython deps (Pipfile format)When present
package.jsonnpm deps: dependencies / devDeps / peerDepsWhen present
scripts/*.py AST scanImplicit Python imports (non-stdlib only)When present
_meta.json / .clawhub/origin.jsonslug, version, registryWhen present
clawhub API (online)stars, downloads, moderation verdict, ownerOptional

Graph Relations

RelationMeaning
belongs_to_categoryskill belongs to a functional category
requires_packageskill depends on a pypi / npm package
uses_toolskill uses a detected tool (heuristic)
requires_toolskill requires a system binary (metadata.requires.bins)
invoked_viaskill is called through a tool channel (allowed-tools)
depends_on_skillskill references another skill in its description

Default Scan Paths

The ingest script checks these locations by default:

  • ~/.openclaw/skills
  • ~/.openclaw/extensions (extensions exposing their own skills via <plugin>/skills/*)
  • /Applications/OpenClaw.app/Contents/Resources/skills (macOS app bundle, when installed)

In addition, ingest scan augments the user-provided or default --dirs arguments with:

  • <project_root>/skills — project-local skills folder when this skill lives

inside a repository

  • $(npm root -g)/openclaw/skills — globally installed OpenClaw skills from

a Node.js / npm environment

Any directory containing a SKILL.md file is treated as a skill.

Ontology Contract

ontology:
  reads: [Skill, SkillCategory, Tool, SoftwarePackage]
  writes: [Skill, SkillCategory, Tool, SoftwarePackage]
  storage: memory/skillchain/graph.jsonl
  schema: schema/skillchain.yaml
  preconditions:
    - "At least one local skill directory is accessible"
  postconditions:
    - "Every discovered skill has a Skill entity"
    - "Skills with requirements.txt have SoftwarePackage entities and requires_package relations"

Storage

Graph data is written to memory/skillchain/graph.jsonl using the same append-only JSONL format as the ontology skill. Reuse scripts/ontology.py from the ontology skill for low-level graph operations.

References

  • references/model.md — Full ontology model (types, relations, constraints)
  • schema/skillchain.yaml — Machine-readable schema for validation

平台分布

OpenClaw

86.05%
按下载量换算2,100

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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