用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/BEKO2210/Firstbrain --skill graph命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | graph |
| description | Knowledge graph analysis -- statistics, clusters, paths, bridges, PageRank |
| version | 3.0.0 |
| triggers | ["/graph"] |
| type | skill |
| tags | ["skill","agent","discovery","graph","analysis"] |
Builds a directed graph from vault notes and their wiki-links, then runs graph algorithms to reveal structure, importance, and hidden patterns.
/graph → Full graph statistics
/graph clusters → Topic clusters by shared tags
/graph rank → Top notes by PageRank importance
/graph path "Note A" "Note B" → Shortest path between two notes
/graph bridges → Notes that connect otherwise separate groups
/graph similar "Note" → Notes with similar connection patterns
/graph hops "Note" → Hidden connections 2-3 hops away
ensureFreshIndexes('.') from scan utils (rebuild if stale)loadAndBuild('.') from graph-engine.cjs to construct the graph| Command | Algorithm | What it reveals |
|---|---|---|
| (default) | graphStats() | Node/edge count, density, components, degree distribution, orphans |
| clusters | findTagClusters() | Groups of 3+ notes sharing the same tag |
| rank | pageRank() | Notes ranked by structural importance (link authority) |
| path | shortestPath() | Minimum hops between any two notes |
| bridges | findBridgeNotes() | Notes whose removal would split the graph |
| similar | findStructurallySimilar() | Notes linking to/from the same neighbors (Jaccard similarity) |
| hops | findMultiHopConnections() | Notes reachable in 2-3 hops but not directly linked |
const { loadAndBuild, graphStats, pageRank, findTagClusters, shortestPath,
findBridgeNotes, findStructurallySimilar, findMultiHopConnections
} = require('./.agents/skills/graph/graph-engine.cjs');
const { ensureFreshIndexes } = require('./.agents/skills/connect/connect-utils.cjs');
Results are presented as formatted text tables. Example:
Knowledge Graph | 57 nodes, 238 edges
Density: 0.074 (sparse -- room to grow)
Components: 2 (1 main + 1 isolated)
Avg degree: 8.35 links per note
Top 5 by PageRank:
1. Home (0.082)
2. Universal AI Clothing Kit (0.041)
3. Projects MOC (0.038)
...