evolve
Propose, evaluate, apply or roll back an evidence-linked skill improvement.
Compile, lint, or query the wiki's typed graph layer.
> /plugin marketplace add praneybehl/llm-wiki-plugin > /plugin install llm-wiki@llm-wiki
How it fires
How this command gets triggered: by you, by Claude, or both.
/graphContext preview
What this command does when you run it.
Compile, lint, or query the wiki's typed graph layer.
description: Compile, lint, or query the wiki's typed graph layer. argument-hint: "extract | lint | neighbors --node <id> | edges --subject <id> | path --from <id> --to <id> | facts --about <id>"
Run a graph-layer operation against the wiki using the `llm-wiki` skill's graph workflow.
Arguments: $ARGUMENTS
0. Resolve `<WIKI_ROOT>` from an explicit user path, the nearest project instructions, global agent instructions, or finally the current project's `wiki/`. Never assume `${PWD}/wiki` when instructions name another wiki. 1. Confirm `<WIKI_ROOT>/graph/ontology.yaml` exists. If not, the wiki is pre-graph — offer to seed its `graph/` directory (copy the templates from `skills/llm-wiki/assets/`) before doing anything else. Do not fabricate ontology entries. 2. Dispatch on the first argument:
3. For query subcommands, after running the script, follow the most relevant edges back to their wiki pages and summarize. Cite with `[[wikilinks]]` to wiki pages, not graph rows. The graph accelerates navigation; the wiki page and its raw source remain the evidence. 4. For `lint`, present findings as proposed edits — do not silently rewrite typed `graph.relationships`. After approved fixes, suggest re-running `extract` so the compiled artifacts stay in sync with the markdown. 5. If `graph.sqlite` is older than the most recent ingest line in `log.md`, suggest running `extract` first.
Full reference: `skills/llm-wiki/references/graph-workflow.md`.
Turn PDFs, articles, transcripts, and notes into a shared wiki that your AI agents can search, cite, and keep up to date. Add a source once. Ask questions later. Keep the useful answers.
Repo: praneybehl/llm-wiki-plugin
Propose, evaluate, apply or roll back an evidence-linked skill improvement.
Ingest a source (paper, article, transcript, PDF, notes) into the LLM Wiki.
Capture verified task experience and consolidate reusable lessons in the wiki.
Query the LLM Wiki — answer a question from accumulated knowledge with citations.