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Knowledge graph and smart memory management using graphify + Obsidian-inspired patterns. Use when: setting up a knowledge graph, managing memory health, cross-linking notes, compiling wiki pages from scattered notes, adding structured frontmatter, or running memory health checks. Triggers on: 'kn...
--- name: knowledge-graph description: "Knowledge graph and smart memory management using graphify + Obsidian-inspired patterns. Use when: setting up a knowledge graph, managing memory health, cross-linking notes, compiling wiki pages from scattered notes, adding structured frontmatter, or running memory health checks. Triggers on: 'knowledge graph', 'graphify', 'wiki', 'cross-link', 'memory health', 'frontmatter', 'compile notes', 'wikilinks'." --- # Knowledge Graph Skill Turn any workspace into a queryable knowledge graph with smart memory management. Combines graphify (code/doc graph) with three Obsidian-inspired patterns. ## Installation In pa-skills repo, the skill is at the *root*: `pa-skills/knowledge-graph/` (not under `skills/`). Copy it to your workspace: ```bash # From your pa-skills clone cp -r knowledge-graph/ /path/to/your/workspace/skills/knowledge-graph/ ``` ## Prerequisites ```bash pip install graphifyy graphify claw install # ⚠️ This MODIFIES your AGENTS.md — adds graphify query rules ``` **Important:** `graphify claw install` appends a `## graphify` section to your AGENTS.md. This is intentional — it tells your agent to check the graph before reading raw files. Review the changes after running it. ## .graphifyignore Create `.graphifyignore` in your workspace root to exclude noise: ``` node_modules/ .git/ media/ .tmp/ tmp/ graphify-out/ pa-skills/ skills-external/ *.pdf *.ogg *.jpg *.png ``` **Critical:** If you have both `pa-skills/knowledge-graph/` and `skills/knowledge-graph/` on disk, add `pa-skills/` to `.graphifyignore` to avoid duplicate nodes in the graph. If your repo clone lives under `.tmp/pa-skills/`, exclude `.tmp/` too or the duplicate noise will still leak in. ## Components ### 1. Knowledge Graph (graphify) Build and query a knowledge graph from code + docs. ```bash # Initial setup (AST-only, free) graphify update . # Query the graph graphify query "how does X connect to Y" graphify path "ModuleA" "ModuleB" graphify explain "concept" # After code changes graphify update . ``` Full semantic extraction (with LLM) produces richer cross-doc connections. See `graphify claw install` output for AGENTS.md integration rules. ### 2. Auto Cross-Linker Scans notes and adds [[wikilinks]] for known concepts from the graph. ```bash # Build concept index from graph nodes + skills + projects python3 scripts/wiki_crosslinker.py --build-index # Cross-link today's daily note python3 scripts/wiki_crosslinker.py --daily # Cross-link all daily notes python3 scripts/wiki_crosslinker.py --all-daily ``` Concepts come from: graphify nodes, skill names, project names, contacts. Only links document-type nodes with 4+ character names. Skips code internals. ### 3. Wiki Compiler (Karpathy Pattern) "Compile once, query forever" — instead of RAG every time, compile scattered mentions into structured wiki pages per topic. ```bash # See what needs compiling python3 scripts/wiki_compiler.py --scan # Compile all topics with 3+ mentions python3 scripts/wiki_compiler.py --compile # Compile one specific topic python3 scripts/wiki_compiler.py --compile "onboarding" # Check wiki status python3 scripts/wiki_compiler.py --status ``` Output: `wiki/<topic>.md` with frontmatter, timeline of mentions, and graph connections. Each page is a self-contained summary — query it directly instead of scanning raw notes. ### 4. Structured Frontmatter Adds YAML frontmatter with auto-detected tags to notes. ```bash # Add frontmatter to all daily notes python3 scripts/note_frontmatter.py --all-daily # Add frontmatter to project docs python3 scripts/note_frontmatter.py --projects # Query by frontmatter python3 scripts/note_frontmatter.py --query tag=onboarding python3 scripts/note_frontmatter.py --query type=project ``` Auto-tags: graphify, crons, ops, whatsapp, calendar, content, monday, onboarding, pa-network, infra, memory, eval, self-improve, skills, owner. ### 5. Memory Health Checker Runs on the knowledge graph to detect memory problems. ```bash # Full report python3 scripts/memory_health.py # Quick summary python3 scripts/memory_health.py --quick ``` Checks: orphan nodes, daily note gaps, stale MEMORY.md entries, weak communities, unreferenced skills, recent vs old activity. ## Recommended Crons ``` # Daily: memory health check (04:00 UTC) daily-memory-health: python3 scripts/memory_health.py --quick # Weekly: wiki compilation + cross-linking (Sun 03:00 UTC) weekly-wiki-compile: 1. python3 scripts/wiki_crosslinker.py --build-index 2. python3 scripts/wiki_compiler.py --compile 3. python3 scripts/note_frontmatter.py --all-daily 4. python3 scripts/note_frontmatter.py --projects 5. graphify update . ``` ## Token Impact | Operation | Without | With | Reduction | |-----------|---------|------|-----------| | Topic recall | ~15K tokens (scan daily notes) | ~200 tokens (wiki page) | 75x | | Architecture query | ~411K tokens (read all files) | ~155 tokens (graph query) | 2,655x | | "What happened with X" | grep all notes | frontmatter query + wiki page | ~50x |--- name: knowledge-graph description: "Knowledge graph and smart memory management using graphify + Obsidian-inspired patterns. Use when: setting up a knowledge graph, managing memory health, cross-linking notes, compiling wiki pages from scattered notes, adding structured frontmatter, or running memory health checks. Triggers on: 'knowledge graph', 'graphify', 'wiki', 'cross-link', 'memory health', 'frontmatter', 'compile notes', 'wikilinks'." --- # Knowledge Graph Skill Turn any workspace into a queryable knowledge graph with smart memory management. Combines graphify (code/doc graph) with three Obsidian-inspired patterns. ## Installation In pa-skills repo, the skill is at the *root*: `pa-skills/knowledge-graph/` (not under `skills/`). Copy it to your workspace: ```bash # From your pa-skills clone cp -r knowledge-graph/ /path/to/your/workspace/skills/knowledge-graph/ ``` ## Prerequisites ```bash pip install graphifyy graphify claw install # ⚠️ This MODIFIES your AGENTS.md — adds graphify query rules ``` **Important:** `graphify claw install` appends a `## graphify` section to your AGENTS.md. This is intentional — it tells your agent to check the graph before reading raw files. Review the changes after running it. ## .graphifyignore Create `.graphifyignore` in your workspace root to exclude noise: ``` node_modules/ .git/ media/ .tmp/ tmp/ graphify-out/ pa-skills/ skills-external/ *.pdf *.ogg *.jpg *.png ``` **Critical:** If you have both `pa-skills/knowledge-graph/` and `skills/knowledge-graph/` on disk, add `pa-skills/` to `.graphifyignore` to avoid duplicate nodes in the graph. If your repo clone lives under `.tmp/pa-skills/`, exclude `.tmp/` too or the duplicate noise will still leak in. ## Components ### 1. Knowledge Graph (graphify) Build and query a knowledge graph from code + docs. ```bash # Initial setup (AST-only, free) graphify update . # Query the graph graphify query "how does X connect to Y" graphify path "ModuleA" "ModuleB" graphify explain "concept" # After code changes graphify update . ``` Full semantic extraction (with LLM) produces richer cross-doc connections. See `graphify claw install` output for AGENTS.md integration rules. ### 2. Auto Cross-Linker Scans notes and adds [[wikilinks]] for known concepts from the graph. ```bash # Build concept index from graph nodes + skills + projects python3 scripts/wiki_crosslinker.py --build-index # Cross-link today's daily note python3 scripts/wiki_crosslinker.py --daily # Cross-link all daily notes python3 scripts/wiki_crosslinker.py --all-daily ``` Concepts come from: graphify nodes, skill names, project names, contacts. Only links document-type nodes with 4+ character names. Skips code internals. ### 3. Wiki Compiler (Karpathy Pattern) "Compile once, query forever" — instead of RAG every time, compile scattered mentions into structured wiki pages per topic. ```bash # See what needs compiling python3 scripts/wiki_compiler.py --scan # Compile all topics with 3+ mentions python3 scripts/wiki_compiler.py --compile # Compile one specific topic python3 scripts/wiki_compiler.py --compile "onboarding" # Check wiki status python3 scripts/wiki_compiler.py --status ``` Output: `wiki/<topic>.md` with frontmatter, timeline of mentions, and graph connections. Each page is a self-contained summary — query it directly instead of scanning raw notes. ### 4. Structured Frontmatter Adds YAML frontmatter with auto-detected tags to notes. ```bash # Add frontmatter to all daily notes python3 scripts/note_frontmatter.py --all-daily # Add frontmatter to project docs python3 scripts/note_frontmatter.py --projects # Query by frontmatter python3 scripts/note_frontmatter.py --query tag=onboarding python3 scripts/note_frontmatter.py --query type=project ``` Auto-tags: graphify, crons, ops, whatsapp, calendar, content, monday, onboarding, pa-network, infra, memory, eval, self-improve, skills, owner. ### 5. Memory Health Checker Runs on the knowledge graph to detect memory problems. ```bash # Full report python3 scripts/memory_health.py # Quick summary python3 scripts/memory_health.py --quick ``` Checks: orphan nodes, daily note gaps, stale MEMORY.md entries, weak communities, unreferenced skills, recent vs old activity. ## Recommended Crons ``` # Daily: memory health check (04:00 UTC) daily-memory-health: python3 scripts/memory_health.py --quick # Weekly: wiki compilation + cross-linking (Sun 03:00 UTC) weekly-wiki-compile: 1. python3 scripts/wiki_crosslinker.py --build-index 2. python3 scripts/wiki_compiler.py --compile 3. python3 scripts/note_frontmatter.py --all-daily 4. python3 scripts/note_frontmatter.py --projects 5. graphify update . ``` ## Token Impact | Operation | Without | With | Reduction | |-----------|---------|------|-----------| | Topic recall | ~15K tokens (scan daily notes) | ~200 tokens (wiki page) | 75x | | Architecture query | ~411K tokens (read all files) | ~155 tokens (graph query) | 2,655x | | "What happened with X" | grep all notes | frontmatter query + wiki page | ~50x |
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Includes source scripts; review them before use. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.