maintainer
Meta-skill that loads all llmwiki governance docs and exposes the three maintainer slash commands.
Review and triage candidate wiki pages — promote, merge, or discard.
> /plugin marketplace add Pratiyush/llm-wiki > /plugin install llmwiki@llmwiki
How it fires
How this command gets triggered: by you, by Claude, or both.
/wiki-candidatesContext preview
What this command does when you run it.
Review and triage candidate wiki pages — promote, merge, or discard.
Review and triage candidate wiki pages — promote, merge, or discard.
Candidate pages live under `wiki/candidates/<kind>/<slug>.md` and were created by `/wiki-ingest` for new entities/concepts the LLM detected. They are **not** part of the trusted wiki layer until a human approves them.
Usage: `/wiki-review`
1. List all pending candidates:
python3 -m llmwiki candidates list
Or filter to stale (age > 30 days):
python3 -m llmwiki candidates list --stale
2. For each candidate, decide:
Moves it into the trusted tree (`wiki/entities/` or `wiki/concepts/`) and rewrites `status: candidate` → `status: reviewed`.
python3 -m llmwiki candidates promote --slug MyEntity
Appends the candidate's body under a `## Candidate merge — <date>` heading in the target page, then archives the candidate.
python3 -m llmwiki candidates merge --slug DuplicateFoo --into Foo
Moves it to `wiki/archive/candidates/<timestamp>/` with a `.reason.txt` audit-trail file.
python3 -m llmwiki candidates discard --slug BogusEntity \
--reason "not a real company; LLM hallucinated"3. After any promote/merge, run `/wiki-lint` to catch broken wikilinks from pages that used to point at the candidate location.
4. Append to `wiki/log.md`:
## [YYYY-MM-DD] review | <N> promoted, <M> merged, <K> discarded
LLM-powered knowledge base from your Claude Code, Codex CLI, Cursor, Gemini CLI, and Obsidian sessions. Built on Andrej Karpathy's LLM Wiki pattern.
Repo: Pratiyush/llm-wiki
Meta-skill that loads all llmwiki governance docs and exposes the three maintainer slash commands.
Run the canonical llmwiki code review against a pull request and post findings.
Apply labels + milestone + priority to a new issue using the llmwiki triage rules.
Run the full llmwiki pipeline end-to-end: build → graph → export all → lint.