Who it is forA team lead or maintainer who relies on agent-written notes and wants to confirm they are tagged and governed before trusting them.
The problemAgent-written notes accumulate without clear sources or confidence levels, so nobody knows which entries to trust.
The outcomeA provenance check and a governance benchmark that list where notes lack source or confidence tags and give an overall score.
What you need first
- Python to run the standard-library scripts
- bash to run vault-init.sh
- A cloud-synced directory on your machine
- An AI agent that can read SKILL.md and follow its lifecycle SOP
Steps
- Run the provenance check on the knowledge base:
python3 ~/.workbuddy/skills/shared-memory-vault/scripts/provenance-check.py(inferred, check the README) - Read the list of notes flagged for missing provenance or confidence tags.
- Run the governance benchmark:
python3 ~/.workbuddy/skills/shared-memory-vault/scripts/governance-score.py(inferred, check the README) - Fix the flagged notes, then rerun the benchmark to confirm the score improves.
Prompt for your agent
Using the shared-memory-vault repo, run its provenance check and governance benchmark on the knowledge base at <knowledge base path>. Report the governance score and the number of notes flagged for provenance. Verify the score by rerunning the benchmark after any fixes.
Caveat. The README names these scripts but does not show their command-line arguments, so the commands above are inferred and should be checked against the script headers.
Use this in your AI agent
Ask your agent
Using the Deduped MCP, get the setup steps for songs-aaa/shared-memory-vault and "Score a knowledge base for governance and provenance"
Add Deduped to Claude Code once
claude mcp add --transport http deduped https://dedupedai.com/mcp
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