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mindgraphmindgraph 分析

Agent Skill

mindgraph 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。

总安装

18,066

周安装

738

GitHub Stars

公开资料未说明

下载量

5,786
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:mindgraph(mindgraph 分析)
来源仓库:https://github.com/hulkworks/mindgraph
安装命令:
openclaw skills install mindgraph
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 mindgraph

简介

使用可学习、可重复的 MindSkills 创建和查询黑曜石风格的 [[wikilink]] 知识图,用于管理和分析工作区文件。

SKILL.md

name
mindgraph
description
Obsidian-style [[wikilink]] knowledge graph and learnable MindSkills for OpenClaw workspaces. Use for ALL of these: (1) Any workspace file read/write — always use [[wikilinks]] for people, projects, tools, concepts. (2) Running learned processes like knockout-test, seo-validator, competitor-analysis. (3) Querying knowledge — "what do I know about X", "show connections to Y". (4) Learning new repeatable processes — "learn a new mindskill called Z". (5) Memory maintenance — finding orphans, dead links, unconnected files. This skill is always active — treat [[wikilinks]] as standard practice in every markdown file you write.

MindGraph 🕸️🧠

A knowledge graph + learnable process engine for OpenClaw. Two core features:

  1. Knowledge Graph — Obsidian-style [[wikilinks]] across all workspace files
  2. MindSkills — Learned, repeatable processes that save graph-connected results

Always-On Rules

Every time you write or edit a markdown file, use [[wikilinks]] for:

  • People: [[Alice]], [[Bob]]
  • Projects: [[my-saas]], [[landing-page]]
  • Companies/tools: [[Stripe]], [[Vercel]], [[GitHub]]
  • Concepts/frameworks: [[Knockout Test]], [[B2B SaaS]]
  • Other agents/models: [[Claude Code]], [[Sonnet]]

This is not optional. Links are how knowledge connects. No links = isolated notes = useless.

NEVER use [[wikilinks]] in messages to the user (Telegram, Discord, etc.). Wikilinks are for workspace files only. In conversations, write names plain: "Alice", not "[[Alice]]".

After significant file changes, rebuild the index:

python3 skills/mindgraph/scripts/mindgraph.py index

Graph Commands

# Build/rebuild index
python3 skills/mindgraph/scripts/mindgraph.py index

# Query a topic (backlinks + context + connections)
python3 skills/mindgraph/scripts/mindgraph.py query "<name>"

# Backlinks only (what references this?)
python3 skills/mindgraph/scripts/mindgraph.py backlinks "<name>"

# Forward links (what does this link to?)
python3 skills/mindgraph/scripts/mindgraph.py links "<file>"

# Bidirectional connections
python3 skills/mindgraph/scripts/mindgraph.py connections "<name>"

# ASCII tree visualization
python3 skills/mindgraph/scripts/mindgraph.py tree "<name>" [depth]

# Find orphans, dead links, unconnected files
python3 skills/mindgraph/scripts/mindgraph.py orphans
python3 skills/mindgraph/scripts/mindgraph.py deadlinks
python3 skills/mindgraph/scripts/mindgraph.py lonely

# Full statistics
python3 skills/mindgraph/scripts/mindgraph.py stats

MindSkills — Learned Processes

MindSkills are repeatable frameworks stored in skills/mindgraph/mindskills/. Each has a defined process and saves results as graph-connected markdown.

Using a MindSkill

# List all learned mindskills
python3 skills/mindgraph/scripts/mindgraph.py skills

# Show a mindskill's process
python3 skills/mindgraph/scripts/mindgraph.py skill <name>

# List results for a mindskill
python3 skills/mindgraph/scripts/mindgraph.py results <name>

When a user asks to run a process (e.g., "run the knockout test on X"), follow this flow:

  1. Read the mindskill's PROCESS.md for the process definition
  2. Execute the process conversationally
  3. Save the result to skills/mindgraph/mindskills/<name>/results/<subject>.md
  4. Use [[wikilinks]] throughout the result file
  5. Include YAML frontmatter with metadata
  6. Rebuild the graph index

Result file template:

---
mindskill: <skill-name>
subject: <what was tested/analyzed>
date: <YYYY-MM-DD>
verdict: <outcome>
aliases: [<aliases>]
---
# [[<MindSkill Name>]]: [[<Subject>]]

<Results following the process defined in PROCESS.md>

## Connections
- Related: [[link1]], [[link2]]

Learning a New MindSkill

When a user says "learn a mindskill called X" or describes a repeatable process:

# Create a new mindskill
python3 skills/mindgraph/scripts/mindgraph.py learn "<name>"

This creates the directory structure. Then write the PROCESS.md based on the user's description.

A good PROCESS.md contains:

  • Purpose: What this process does and when to use it
  • Trigger phrases: What the user might say to invoke this
  • Steps: The actual process to follow (numbered)
  • Output format: What the result file should contain
  • Verdict/scoring: How to summarize the outcome (if applicable)

Discovering MindSkills

When a user's request matches a learned mindskill, proactively suggest it:

  • "Want me to run the [[Knockout Test]] on that?"
  • "I have an [[SEO Validator]] mindskill — should I audit that?"
  • "This looks like a [[Competitor Analysis]] — want the full framework?"

Link Resolution

Links match (case-insensitive) against:

  1. File basenames: [[MEMORY]]MEMORY.md
  2. Project dirs: [[my-saas]]projects/my-saas/
  3. MindSkill results: [[Pet Tracker KT]] → knockout test result
  4. YAML aliases: aliases: [AV-Check][[AV-Check]] resolves
  5. Unresolved → concept node (still tracked for backlinks)

File Locations

  • Graph index: mindgraph.json (workspace root)
  • MindSkills: skills/mindgraph/mindskills/
  • Script: skills/mindgraph/scripts/mindgraph.py

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

92.56%
按下载量换算5,356

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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