Skill: brianhearn/obsidian-to-expertpack (version 1.0.1)

--- name: obsidian-to-expertpack description: "Convert an existing Obsidian Vault into an agent-ready ExpertPack. Restructures vault content for EK optimization, RAG retrieval, and OpenClaw integration. Creates a copy — source vault is never modified. Use when: a user wants to make their Obsidian Vault usable by AI agents, convert OV to EP, drop their vault into OpenClaw as a knowledge pack, or make their notes RAG-ready. Triggers on: 'obsidian to expertpack', 'obsidian vault to ep', 'convert obsidian', 'OV to EP', 'obsidian agent ready', 'make my vault ai ready', 'obsidian knowledge pack', 'obsidian rag'." metadata: openclaw: homepage: https://expertpack.ai requires: bins: - python3 pip: - pyyaml --- # Obsidian Vault → ExpertPack Converts an Obsidian Vault into a structured **ExpertPack** — agent-ready, RAG-optimized, and OpenClaw-compatible. Source vault is never modified; output is a clean copy. **Learn more:** [expertpack.ai](https://expertpack.ai) · [GitHub](https://github.com/brianhearn/ExpertPack) > **Companion skills:** Install `expertpack` for full EP workflows. Install `expertpack-eval` to measure EK ratio after conversion. ## Step 1: Analyze the Vault Before running the script, inspect the vault: 1. List the top-level directories — these map to EP content sections 2. Identify the **pack type** based on structure: - `journals/`, `daily/`, `people/`, `mind/` → **person** - `concepts/`, `workflows/`, `troubleshooting/`, `faq/` → **product** - `phases/`, `checklists/`, `decisions/`, `steps/` → **process** - Mix of the above → **composite** 3. Note any `templates/` or `_templates/` folders — exclude from conversion 4. Estimate content volume and identify the highest-EK directories The script auto-detects type (`--type auto`) but verify your judgment matches before proceeding. See `references/migration-guide.md` for the full decision tree. ## Step 2: Run the Conversion Script ```bash python3 /path/to/ExpertPack/skills/obsidian-to-expertpack/scripts/convert.py \ /path/to/obsidian-vault \ --output ~/expertpacks/my-pack-slug \ --name "My Pack Name" \ [--type auto|person|product|process|composite] \ [--dry-run] ``` Always do a `--dry-run` first to preview what will be converted. **What the script produces:** - All `.md` files copied with EP frontmatter (`title`, `type`, `tags`, `pack`, `created`) - Inline `#hashtags` extracted into frontmatter `tags:` - Dataview query blocks stripped (computed views, not knowledge) - `[text](file.md)` links converted to `[[wikilinks]]` - `manifest.yaml`, `overview.md`, `glossary.md` at pack root - `_index.md` in each content directory - `.obsidian/` config copied (pack opens in Obsidian immediately) For detailed handling of Obsidian-specific patterns (nested tags, daily notes, templates, attachments): read `references/migration-guide.md`. ## Step 3: Validate & Fix ```bash # Fix common issues first python3 /path/to/ExpertPack/tools/validator/ep-doctor.py ~/expertpacks/my-pack-slug --apply # Must reach 0 errors python3 /path/to/ExpertPack/tools/validator/ep-validate.py ~/expertpacks/my-pack-slug --verbose # Fix any broken wikilinks (cross-vault references) python3 /path/to/ExpertPack/tools/validator/ep-fix-broken-wikilinks.py ~/expertpacks/my-pack-slug --apply ``` Do not proceed until `ep-validate` reports **0 errors**. ## Step 4: Agent-Assisted Enhancement After validation, enhance retrieval quality: 1. **Lead summaries** — add a 1-3 sentence blockquote at the top of the 5-10 most important files 2. **Glossary** — populate `glossary.md` with domain-specific terms (this is Tier 1 — always loaded) 3. **Propositions** — create `propositions/` with atomic factual statements extracted from high-EK files 4. **EK triage** — identify low-EK files (general knowledge) and compress or remove them 5. **File size** — split files >3KB on `##` header boundaries ## Step 5: Configure RAG in OpenClaw Add to `~/.openclaw/openclaw.json`: ```json { "agents": { "defaults": { "memorySearch": { "extraPaths": ["/path/to/your/converted-pack"] } } } } ``` Restart OpenClaw after config change. The pack is now searchable in every session. ## Step 6: Measure EK Ratio ```bash clawhub install expertpack-eval ``` Run evals to score how much esoteric knowledge the pack contains vs. what the model already knows. Target EK ratio >0.6 for high-value packs.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)