ExpertPack

Structured knowledge packs for AI agents. Maximize the knowledge your AI is missing.

Learn more: expertpack.ai · GitHub · Schema docs · Obsidian compatible

💎 Obsidian compatible: Every ExpertPack is a valid Obsidian vault. Copy the

.obsidian/

folder from the ExpertPack repo

template/

directory into your pack root, open it in Obsidian, and install Dataview + Templater. You get live queries by content type, EK score, and tags; graph view; and full-text search. Standard relative Markdown links — packs render correctly on GitHub and in Obsidian simultaneously.

Companion skills: This skill covers consumption and hydration guidance only. For CLI tooling (validate, doctor, graph export, frontmatter strip) use

expertpack-cli

. For EK measurement and quality evals use

expertpack-eval

. For exporting an OpenClaw agent's workspace as an ExpertPack use

expertpack-export

. For converting an existing Obsidian Vault into an agent-ready ExpertPack use

obsidian-to-expertpack

. For serving a pack as an MCP endpoint (expertise-as-a-service), see EP MCP — a generic MCP server for any ExpertPack.

Full schemas:

/path/to/ExpertPack/schemas/

in the repo (core.md, person.md, product.md, process.md, composite.md, eval.md)

Pack Location

Default directory:

~/expertpacks/

. Check there first, fall back to current workspace. Users can override by specifying a path.

Actions

1. Load / Consume a Pack

1. Read

   manifest.yaml

   — identify type, version, context tiers
2. Read

   overview.md

   — understand what the pack covers
3. Load all Tier 1 (always) files into session context
4. For queries: search Tier 2 (searchable) files via RAG or

   _index.md

   navigation
5. Load Tier 3 (on-demand) only on explicit request (verbatim transcripts, training data)

To configure OpenClaw RAG, point

memorySearch.extraPaths

in

openclaw.json

at the pack directory. Files are authored at 400–800 tokens each — retrieval-ready by design.

For detailed platform integration (Cursor, Claude Code, custom APIs, direct context window): read

{skill_dir}/references/consumption.md

.

Volatile files: If a pack uses

volatile/

files with a

source

URL, staleness is checked at session start and the agent alerts you. Refresh is always user-initiated — no automatic background network fetches occur.

2. Create / Hydrate a Pack

1. Determine pack type: person, product, process, or composite
2. Read

   {skill_dir}/references/schemas.md

   for structural requirements
3. Create root directory using the pack slug (kebab-case)
4. Obsidian setup (optional): Copy the

   .obsidian/

   folder from the

   template/

   directory in the public ExpertPack repo (github.com/brianhearn/ExpertPack) into the pack root — the user can do this manually to get Dataview + Templater pre-configured.
5. Create

   manifest.yaml

   and

   overview.md

   (both required)
6. Scaffold content directories per the type schema with

   _index.md

   in each
7. Populate content using EK-aware hydration:
   • Focus on esoteric knowledge — content the model cannot produce on its own
   • Full treatment for EK content; compressed scaffolding for general knowledge
   • Skip content with zero EK value
8. Add retrieval layers:

   summaries/

   ,

   propositions/

   ,

   glossary.md

   , lead summaries in content files
9. Add

   sources/_coverage.md

   documenting what was researched

For full hydration methodology and source prioritization: read

{skill_dir}/references/hydration.md

.

3. Configure RAG

Point OpenClaw RAG at the pack directory via

openclaw.json

(

memorySearch.extraPaths

). See

{skill_dir}/references/consumption.md

for the exact config. No external chunking tool needed — files are authored at 400–800 tokens by design.

4. Measure EK Ratio & Run Quality Evals

Install the companion skill

expertpack-eval

via clawhub — it handles all LLM API calls for blind probing and eval scoring.

5. Validate & Fix a Pack

Install the companion skill

expertpack-cli

via clawhub — it provides ep-validate, ep-doctor, ep-graph-export, and ep-strip-frontmatter with full command syntax and workflows.

6. Export an OpenClaw Agent as an ExpertPack

Install the companion skill

expertpack-export

via clawhub — it handles workspace scanning, distillation, and packaging.