repo-mission-portfolio-audit
Audit the workspace-hub repo portfolio to extract each repo's mission, identify documentation gaps, and prioritize a plan/approval sequence with explicit LLM-wiki weighting for future issue triage.
Best use case
repo-mission-portfolio-audit is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Audit the workspace-hub repo portfolio to extract each repo's mission, identify documentation gaps, and prioritize a plan/approval sequence with explicit LLM-wiki weighting for future issue triage.
Teams using repo-mission-portfolio-audit should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/repo-mission-portfolio-audit/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How repo-mission-portfolio-audit Compares
| Feature / Agent | repo-mission-portfolio-audit | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Audit the workspace-hub repo portfolio to extract each repo's mission, identify documentation gaps, and prioritize a plan/approval sequence with explicit LLM-wiki weighting for future issue triage.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Repo Mission Portfolio Audit Use when the user wants a portfolio-wide understanding of what each repo is for, what should be revised first, or how future GitHub issue creation should incorporate repo mission and LLM-wiki value. ## Inputs to gather 1. Cross-session context - Run `session_search` with broad OR terms like: - `repo mission OR adversarial plan OR llm-wiki OR issue planning OR repo portfolio` - Use this to recover prior conclusions, open strategy lanes, and existing planning artifacts. 2. Canonical workspace context - Read: - `docs/BUSINESS_BRAIN.md` - `docs/WORKSPACE_HUB_REPOSITORY_OVERVIEW.md` - root repo overview files - `docs/README.md` - These define tiering, repo roles, and the ecosystem control-plane story. 3. Relevant plan lanes - Read active portfolio/knowledge plans when relevant, especially: - `docs/plans/2026-04-20-issue-2398-llm-wiki-spinout-vs-embedded-architecture.md` - `docs/plans/2026-04-20-issue-2420-repo-portfolio-steering-contract.md` - `docs/plans/2026-04-12-llm-wiki-ecosystem-strengthening-gh-stories.md` - recent handoffs under `docs/handoffs/` and `docs/session-handoffs/` 4. Live repo inventory - Enumerate actual subrepos from the workspace root by checking which immediate child directories contain `.git`. - For each repo, inspect presence of: - workflow contract file - top-level README - provider-specific config file - `.agent-os/product/mission.md` - `.agent-os/product/roadmap.md` - `.agent-os/product/decisions.md` - Also capture git cleanliness when it matters before proposing edits. ## Practical extraction pattern For each repo, derive the mission from the strongest available source in this order: 1. `.agent-os/product/mission.md` 2. `README.md` 3. workflow contract file 4. `docs/README.md` 5. provider-specific config file Record: - repo name - tier (from `docs/BUSINESS_BRAIN.md` if available) - mission summary - source used for the summary - documentation completeness gaps ## Execution pattern after the audit recommendation Use this when the user accepts the audit recommendation and asks to "execute the recommended next moves" or similar. 1. Re-check live GitHub state before acting: - search for an already-open portfolio mission/objective issue to avoid duplicates - view the recommended parent/related issues and record state/title/labels - if a related child issue is already implemented on a branch, check for an existing PR before creating one 2. If no suitable portfolio-wide issue exists, create one with a class-level title such as `feat(repo-portfolio): review and revise mission/objective statements across active repos`. 3. The new issue body should include: - Tier-1/Tier-2/Tier-3 starting inventory from `docs/BUSINESS_BRAIN.md` - deliverables for a canonical portfolio mission artifact, classification, source evidence, routing rules, and overlap/conflict notes - related links to the umbrella/structure/routing issues already found - explicit planning-gate language: issue -> resource intel -> plan -> adversarial review -> plan-review -> user approval -> plan-approved -> implementation 4. Immediately draft the repo-tracked plan under `docs/plans/YYYY-MM-DD-issue-NNN-<slug>.md` and update `docs/plans/README.md` if the repo uses that index. 5. Commit and push the draft plan/index update, then comment on: - the new portfolio issue with plan path + commit + current gate state - parent/related umbrella issues with the new issue link and scope boundary - any still-open child issue with PR/branch evidence if you touched its routing state 6. Do **not** add `status:plan-review` until adversarial review has actually run and the plan summary is populated. Draft-planned means draft only. ## Required synthesis Before recommending new issue creation, explicitly distinguish **repo mission/objective review** from adjacent but different work classes: - **routing/indexing/code-placement** issues answer "where should future work land and be retrieved?" - **mission/objective** issues answer "what is this repo for, what work belongs here, and should the repo remain active, archival, merged, or no-new-issues?" When live GitHub already has a routing/indexing issue family (for example a contract issue plus per-repo routing child issues), do not treat that as complete portfolio mission review. Instead: 1. Verify the live state of the related issues with `gh issue view/list` rather than relying on stale plan/report text. 2. Identify which children are closed, which remain open/working, and whether any freshness report is stale relative to closed issues. 3. Recommend extending an existing umbrella issue when it reasonably owns mission/objective review; otherwise recommend a new portfolio-wide issue titled at the mission/objective class level. 4. For a mission/objective issue, require each repo to be classified as active product/library, client vertical, business/admin support, archive/reference, or deprecated/no-new-issues. 5. Require each repo's output to include both "work belongs here when..." and "work does not belong here when..." rules, plus duplicate/boundary checks between similar repos. Produce these outputs: ### 1. Ecosystem mission model Distill the portfolio into a small set of role classes, typically: - control plane - engineering computation core - shared utility substrate - GTM / externalization layer - domain/client verticals - archives/support repos ### 2. Revision order Recommend a wave-based approval order instead of a flat repo list. Default ordering: 1. `workspace-hub` 2. Tier-1 repos 3. Tier-2 repos 4. Tier-3 repos Explain why each wave comes before the next. ### 3. Documentation gaps Call out missing or weak surfaces, especially: - repos missing a workflow contract file - repos missing a top-level README - repos missing structured `.agent-os/product/*` mission files - repos whose mission is only implied by a pointer file - repos that are too dirty locally to revise safely without state triage ### 4. LLM-wiki weighting rule When the user wants future issue creation to consider knowledge value, explicitly propose a scoring rubric that includes LLM-wiki contribution. A good default issue score is: - 35% repo mission / strategic alignment - 25% execution leverage / downstream impact - 20% LLM-wiki contribution - 10% governance / drift reduction - 10% implementation readiness Define the 20% LLM-wiki component using: - durable knowledge capture - cross-repo usefulness - retrieval/discoverability improvement - promotion-readiness into wiki/docs/routing ## Good output structure Use: 1. High-level conclusion 2. What prior sessions already established 3. Recommended mission-revision order 4. Per-repo mission snapshot by tier/wave 5. Documentation gaps 6. LLM-wiki-weighted issue triage rule 7. Concrete next-step recommendation ## Important cautions - Do not invent repo mission text if no strong source exists; mark it as a gap. - Do not revise files directly unless the user explicitly asks for edits; this audit is usually a planning/approval precursor. - If the workspace root or a target repo is dirty, mention it before recommending direct changes. - Treat unresolved architecture questions (for example LLM-wiki embedded vs spinout) as current-state constraints, not settled facts. ## Reusable conclusion pattern A common portfolio conclusion in this ecosystem is: - `workspace-hub` = control plane - `digitalmodel` = engineering computation core - `assetutilities` = shared utility substrate - `aceengineer-website` = GTM/proof surface - `llm-wikis` = cross-repo durable knowledge layer Use this as a hypothesis only when supported by the current docs and session evidence.
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