mamertofabian/maid-runner/maid-outcome-enrich
Claude Code and agent skill by mamertofabian/maid-runner
- community
Checking that the SKILL.md file is still in the repository.
Generate optional advisory Outcome enrichment outside maid-runner by orchestrating maid enrich prompt, agent-available model generation, maid enrich validate, and maid enrich render with cloud privacy disclosure.
Install
npx vskill@latest install mamertofabian/maid-runner/maid-outcome-enrichSKILL.md
MAID Outcome Enrich
Generate optional advisory Outcome enrichment while keeping maid-runner itself deterministic and AI-free. This skill is the only place in the enrichment workflow that may call a model or touch provider credentials.
Rules
- Keep runner commands deterministic. Use
maid enrichonly for prompt corpus
creation, digest validation, and markdown rendering.
- Use the model access already available to the hosting agent, or a specific model the user chooses.
- CLOUD-PRIVACY: sending the lesson corpus to an external provider publishes Outcome lessons externally. Use external generation only after the user deliberately accepts that privacy boundary.
- A non-zero
maid enrich validateresult is a hard stop. Do not hand-edit.maid/outcomes-digest.jsonto satisfy validation; regenerate the candidate digest from the bounded corpus instead. - Use only registered
maid enrichandmaid insightsoptions. Do not invent
provider, model, base URL, timeout, or API-key options for maid-runner.
Workflow
- Refresh the learned Outcome index when needed:
``bash maid learn ``
- Build the bounded corpus the model may see:
``bash maid enrich prompt --output .maid/outcomes-enrichment-prompt.json ``
If the index is intentionally stale, use the existing explicit opt-in:
``bash maid enrich prompt --allow-stale-index --output .maid/outcomes-enrichment-prompt.json ``
- Send only
.maid/outcomes-enrichment-prompt.jsonto a model.
Use the model access already available to the hosting agent, or a specific model the user chooses. If that sends the corpus to an external provider, disclose CLOUD-PRIVACY first: sending the lesson corpus externally publishes Outcome lessons outside the local repository boundary.
The model output must be a candidate .maid/outcomes-digest.json.
- Validate the candidate digest:
``bash maid enrich validate --digest .maid/outcomes-digest.json ``
Treat a non-zero maid enrich validate result as a hard stop. Do not hand-edit .maid/outcomes-digest.json to satisfy validation. Regenerate the candidate digest from the bounded corpus and validate again.
- Render advisory markdown from the validated digest:
``bash maid enrich render --digest .maid/outcomes-digest.json --md-output .maid/outcomes-digest.md ``
- Optionally view deterministic theme aggregation through insights:
``bash maid insights --theme-map .maid/outcomes-digest.json ``
Output Boundaries
.maid/outcomes-digest.json and .maid/outcomes-digest.md are advisory, generated, ignored artifacts. They are not authoritative Outcome records and must not replace manifest outcome: sections, validation commands, review evidence, or the MAID implementation lifecycle.
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingmaid_runner/codex/skills/maid-outcome-enrich/SKILL.md
Popularity
- Repository stars
- 3
- 7-day trend score
- 0
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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