llm-wiki-ecosystem-gap-to-issues
Review the workspace-hub LLM-wiki/document-intelligence ecosystem, identify high-leverage gaps, and create grounded GitHub feature issues without duplicating existing work.
Best use case
llm-wiki-ecosystem-gap-to-issues is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Review the workspace-hub LLM-wiki/document-intelligence ecosystem, identify high-leverage gaps, and create grounded GitHub feature issues without duplicating existing work.
Teams using llm-wiki-ecosystem-gap-to-issues 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/llm-wiki-ecosystem-gap-to-issues/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How llm-wiki-ecosystem-gap-to-issues Compares
| Feature / Agent | llm-wiki-ecosystem-gap-to-issues | 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?
Review the workspace-hub LLM-wiki/document-intelligence ecosystem, identify high-leverage gaps, and create grounded GitHub feature issues without duplicating existing work.
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
# LLM-wiki ecosystem gap -> GitHub issues
Use when the user asks to review the repo/document ecosystem and create new issues to strengthen LLM-wikis.
## Goal
Turn ecosystem review into a small set of non-duplicate, high-leverage GitHub issues grounded in live repo state rather than intuition.
## Required evidence sources
Read these before proposing issues:
1. Live GitHub issue search
- `gh issue list --search 'llm-wiki OR knowledge wiki OR wiki ingest OR knowledge/wikis'`
- Then narrower searches for the exact candidate theme to avoid duplicates.
2. Architecture / review docs
- `docs/document-intelligence/llm-wiki-resource-doc-intelligence-operating-model.md`
- `docs/reports/2026-04-16-llm-wiki-resource-intelligence-unified-review.md`
3. Priority/execution artifacts
- `docs/reports/llm-wiki-external-source-priority-queue.md`
- `docs/reports/llm-wiki-staged-batch-packs.md`
4. Discoverability / provenance gaps
- `docs/document-intelligence/intelligence-accessibility-map.md`
- `docs/document-intelligence/standards-codes-provenance-reuse-contract.md`
5. Live repo facts
- Count wiki pages directly from `knowledge/wikis/*/wiki/**/*.md`
- Check cross-link artifacts (`knowledge/wikis/cross-links.md`, `cross-links.jsonl` if present)
- Inspect `data/design-codes/code-registry.yaml` when proposing standards/registry-driven strengthening
## Proven issue themes that are worth checking first
These themes produced grounded issue opportunities:
1. `wiki_refs` reverse lookup
- Trigger: architecture/provenance docs define the contract, but live repo still lacks registry -> wiki reverse lookup.
- Signal: accessibility map says affected wiki pages can only be found with grep.
2. External-source promotion packs
- Trigger: priority queue + staged batch pack already exist, but execution issue is missing.
- Signal: thin wiki domains (engineering / naval-architecture / maritime-law) plus metadata-rich source families ready for promotion.
3. Design-code registry promotion into wiki surfaces
- Trigger: `data/design-codes/code-registry.yaml` has rich edition/repo metadata but is not linked from standards wiki surfaces.
4. Wiki strengthening scorecard
- Trigger: health/lint exists, but prioritization across domains/source families is still ad hoc.
5. Large-domain navigation repair
- Trigger: a wiki domain is technically discoverable but functionally unusable because `wiki/index.md` is huge or uncurated.
- Signal: live line counts show monolithic indexes (for example 20k+ lines) and the accessibility map says there is no curated entry beyond the index.
6. Source-title aliasing
- Trigger: source pages exist, but titles are mostly raw filenames or numeric IDs.
- Signal: live sampling/counts show most source-page frontmatter titles look like `spe143317.pdf` or `22035.pdf` instead of human-readable titles.
7. Closed-issue / transient-to-durable promotion substrates
- Trigger: the repo has policy for L5/L6 -> L3 promotion, but not the operational ledger/queue to execute it.
- Signal: broad closed-issue backlog, handoff/review corpora, or WRK completion archives exist without structured promotion routing.
8. Provenance backfill on legacy wiki pages
- Trigger: newer provenance rules (`doc_key`, `promoted_from`, `wiki_refs`) are ahead of older wiki content.
- Signal: existing pages/logs lack deterministic promotion lineage even though the contracts now expect it.
## Parallel-agent sweep pattern
When the user explicitly wants broader recommendation coverage, use parallel subagents to split the search space before creating issues.
Recommended split:
1. Navigation/discoverability surfaces
- Focus on `docs/document-intelligence/README.md`, `intelligence-accessibility-map.md`, `intelligence-accessibility-registry.yaml`, wiki indexes, and cross-link artifacts.
2. Source-ingest / batch-pack execution gaps
- Focus on priority queues, staged batch packs, maturity ledgers, online-resource registries, and transfer ledgers.
3. Tacit-knowledge / repo-intelligence promotion gaps
- Focus on closed issues, handoffs, review artifacts, WRK completion archives, and seed surfaces.
For each subagent:
- keep the task read-only
- require duplicate checks against open issues
- ask for 2-4 issue-ready candidates with labels, scope boundaries, and why they are not duplicates
Then, in the main context:
- synthesize the candidate list
- discard overlap-prone ideas
- keep the issues with the clearest ownership concern and strongest live evidence
- write body files and create the issues yourself so taxonomy/wording stay consistent
## Issue creation pattern
For each candidate issue:
1. Verify non-duplication with a targeted `gh issue list --search ...` query.
2. Pull 2-4 concrete facts from repo artifacts (counts, missing files, explicit gap statements in docs).
3. Write a temp markdown body file with these sections:
- Summary
- Why
- Scope
- Deliverables
- Acceptance Criteria
- Related
4. Prefer labels already in repo taxonomy:
- `enhancement`
- `priority:high|medium`
- one category label such as `cat:data-pipeline`, `cat:documentation`, or `cat:harness`
- one domain label such as `domain:document-intelligence` or `domain:knowledge-management`
5. Create with `gh issue create --body-file ...`
6. Immediately verify the created issue via `gh issue view --json number,title,url,labels,body`
## Writing heuristics
- Create issues that bridge existing architecture to missing implementation, not broad vague ideas.
- Reuse existing queue/plan artifacts when they already define a bounded execution slice.
- Prefer strengthening thin or weakly connected wiki domains over adding more volume to already-dense domains.
- Use live counts in the issue body when they justify prioritization.
- If an adjacent issue already exists but only covers a neighboring layer, create the new issue only if the ownership concern is clearly different.
## Additional proven issue themes from deeper recommendation sweeps
After the first gap-to-issues pass, the following additional themes also produced strong, non-duplicate issues when validated with parallel subagents:
1. Canonical marine-index repair
- Examples: faceted portals, canonical index chunking/pagination, source-title aliasing.
- Signals:
- marine-engineering `wiki/index.md` is ~20k+ lines
- source corpus dominates the domain
- source-page titles are mostly filenames or numeric IDs
2. Batch-pack execution children beyond Pack 1
- Examples: Batch Pack 2 indexed conference-summary promotion, Batch Pack 3 Tier A external engineering software profiles, Batch Pack 4 non-mkt-a standards-summary promotion.
- Important lesson: treat each pack as a separate issue only when the source family, execution mode, and duplicate boundaries are clean.
3. Policy-to-enforcement follow-ons
- Examples: promotion audit-trail checker, GUARD-1 invented-layer detector, recurring-run output pruner, handoff expiration metadata.
- Signals:
- policy docs explicitly name future enforcement/checker surfaces
- repo still contains live examples of the forbidden/unguarded pattern
4. Transient/tacit-knowledge routing substrates
- Examples: transient-promotion candidate queue, closed-issue promotion ledger, WRK completions normalization, provenance backfill.
- Signals:
- repo already has handoffs/review artifacts/WRK archives, but no operational queue or normalized seed surface.
5. Registry-backed discoverability surfaces
- Examples: task/asset explorer from accessibility registry, wiki-index uplink/back-navigation standard.
- Signals:
- navigation metadata exists in YAML/docs, but is not yet exposed as a generated explorer or standard nav surface.
6. Promotion-pipeline traceability plumbing
- Example: thread `source_doc_key` through promoted artifacts alongside `content-hash`.
- Signal:
- contract explicitly distinguishes output integrity vs source traceability, but code still emits only integrity stamps.
## Roadmap / umbrella pattern
When the user wants to continue after multiple issue-creation waves, stop mining for more ideas and switch to execution-structure work.
Recommended next step after ~10+ grounded issues exist:
1. Read the created issues back with `gh issue view`.
2. Use parallel subagents to group them into:
- provenance/governance/foundation
- content-promotion/source-family execution
- navigation/discoverability
3. Synthesize execution waves with:
- hard prerequisites
- soft sequencing preferences
- safe parallel bundles (separate worktrees)
- readiness mismatches discovered during review
4. Create one umbrella issue for roadmap/steering only.
A good umbrella issue should:
- list the child issues by wave
- record prerequisites like schema authority / `doc_key` / `promoted_from`
- note known readiness problems (for example, when a child issue's starter slice mismatches live repo data)
- stay planning-only; do not absorb implementation scope from child issues
## Do-not-file heuristics learned from this sweep
- Do not file a residual source-family issue if the remaining records collapse to a tiny, heterogeneous set after excluding overlap with already-filed batch packs.
- Do not create a navigation issue that overlaps with an existing portal/chunking issue unless the ownership concern is clearly different (for example, cross-wiki nav standard vs large-domain portal generation).
- Do not file broad provenance issues when the repo already has a parent contract issue and the real gap is a specific implementation child.
- When a recommendation depends on unresolved live-data readiness, either narrow the issue or record the mismatch explicitly in the body/roadmap instead of pretending the initial scope is execution-ready.
## Good example candidates
- `feat(doc-intel): materialize wiki_refs reverse lookup from doc_key to citing wiki pages`
- `feat(knowledge): execute Batch Pack 1 to promote API/standards-portal metadata into thin wiki domains`
- `feat(knowledge): promote design-code registry into standards overviews and repo-target backlinks`
- `feat(knowledge): add llm-wiki strengthening scorecard and prioritized action queue`
- `feat(knowledge): generate faceted portal pages for large LLM-wiki domains`
- `feat(knowledge): execute Batch Pack 2 to promote indexed conference summaries into wiki topic stubs`
- `feat(knowledge): build transient-promotion candidate queue from handoffs and review artifacts`
- `feat(conformance): add promotion audit-trail checker for L5/L6→L3 wiki promotions`
- `feat(doc-intel): thread source_doc_key through promotion pipeline and promoted artifacts`
- `epic(knowledge): llm-wiki strengthening roadmap and execution waves`
## Pitfalls
- Do not create duplicates of umbrella/architecture issues when the real gap is an unexecuted child implementation.
- Do not rely on stale remembered wiki counts; count the current repo state.
- Do not pitch raw-source ingest work before checking whether metadata-first or summary-backed promotion is already designed.
- Do not create a generic "improve llm-wiki" issue when the repo already has specific artifacts that justify narrower, executable stories.Related Skills
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