메뉴
Analyze knowledge base structure and update the knowledge-base-analysis.md report
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | analyze-kb |
| description | Analyze knowledge base structure and update the knowledge-base-analysis.md report |
| automation | gated |
| allowed-tools | Read, Bash, Glob, Grep |
Analyze the Obsidian knowledge base structure and regenerate a condensed, manageable analysis report.
Use Local Brain Search for all semantic search operations.
Scripts:
# Semantic search
resources/local-brain-search/run_search.sh "query" --limit 10 --json
# Find connections
resources/local-brain-search/run_connections.sh "Note Name" --json
# Get graph statistics
resources/local-brain-search/run_connections.sh --stats --json
# Find hub notes
resources/local-brain-search/run_connections.sh --hubs --json
# Find bridge notes
resources/local-brain-search/run_connections.sh --bridges --json
Follow these steps:
Get vault statistics using Local Brain Search:
resources/local-brain-search/run_connections.sh --stats --json
List all notes with full directory tree using Bash find:
find $VAULT_BASE_PATH/Brain -name "*.md" -type f | head -50
Use Glob to explore directory structure:
Brain/**/*.mdBrain/02-Permanent/*.mdBrain/03-MOCs/*.mdBrain/01-Sources/**/*.mdRead key hub notes from major clusters using Read tool (Dopamine, Self/Buddhism, Decision-Making, Flow, etc.)
Use Local Brain Search to identify hub notes and bridges:
resources/local-brain-search/run_connections.sh --hubs --json
resources/local-brain-search/run_connections.sh --bridges --json
Fingerprint scope note: --hubs/--bridges are the cognitive-fingerprint
axis. Scope enforcement is now ON (MEMORY_CONFIG['scope']['enforce']=True,
since 2026-06-25; see SCOPE-IMPLEMENTATION-PLAN.md), so they compute on the
core subgraph only (02-Permanent, 03-MOCs, AI Extracted Notes,
01-Sources). Document-Insights-inflated hubs (Dopamine/Flow) no longer appear;
the true core hubs (MOC - Eight-Circuit, Decision Making, Gilbert, Tetlock,
Hagen) surface. --stats stays whole-graph (it answers "how big is the
store", not "who am I"). Note which mode is active when recording hubs.
Pull BDG statistics for layer distribution and lifecycle phases:
resources/brain-graph/run_brain_graph.sh status --json
Analyze thematic clusters, hierarchical organization, and conceptual architecture
Use Edit or Write to update the knowledge-base-analysis.md file with a condensed report (target: ~600-800 lines max):
CRITICAL OUTPUT REQUIREMENTS:
Generate a condensed, scannable, high-signal report that reveals the knowledge base's personality, cognitive fingerprint, and growth opportunities without overwhelming detail.
| Source | Location | Read | Write | Description |
|---|---|---|---|---|
| Brain notes | Brain/**/*.md | X | All vault notes for analysis | |
| Permanent notes | Brain/02-Permanent/ | X | Core insights | |
| MOCs | Brain/03-MOCs/ | X | Map of Content hubs | |
| Sources | Brain/01-Sources/ | X | Reference materials | |
| AI Insights | Brain/AI Extracted Notes/ | X | AI-extracted notes | |
| Document Insights | Brain/Document Insights/ | X | Research session notes | |
| Book scopes | Brain/Books/ | X | Per-book scopes (non-core, family) | |
| Changelogs | Brain/05-Meta/Changelogs/ | X | Session logs | |
| Local Brain Search | resources/local-brain-search/ | X | Graph statistics, hubs, bridges | |
| Knowledge base analysis | knowledge-base-analysis.md | X | X | Output report |
Autonomous AI crystallization - synthesizes converged thinking topics into ai-inferred notes in a dedicated folder. Never touches the human-curated permanent knowledge base and never changes a topic's status, so manual crystallization stays available to the user.
Discover non-obvious cross-domain connections through random sampling and pattern analysis
Run a full coherence sweep across the Brain Dependency Graph - computes staleness, lifecycle transitions, structural health, and generates a report
Compute lifecycle scores for all insight and framework notes - detect which notes are crystallizing or becoming generative
Create long-form articles from knowledge base insights. Use when writing articles, blog posts, Substack content, or synthesizing knowledge into publishable content. Includes tone of voice, structure templates, and knowledge base integration.
Generate explanatory diagrams and infographics that visually communicate concepts. Iterates autonomously until images are logically correct, text is clean, and the concept explanation is clear. Uses Nano Banana (Gemini 2.5 Flash Image).