/lint
Run a structural and semantic health check on the LLM Wiki.
$ npx -y skills add praneybehl/llm-wiki-plugin --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/lint
Context preview
What this command does when you run it.
Run a structural and semantic health check on the LLM Wiki.
Command definition
lint.mddescription: Run a structural and semantic health check on the LLM Wiki.
argument-hint: "[--suggest-pages]"
Run a lint pass on the wiki using the `llm-wiki` skill's lint workflow.
Arguments (if any): $ARGUMENTS
1. Read `wiki/SCHEMA.md` first if you haven't this session — it may declare additional lint rules. 2. Run the structural lint script: `python "${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki/scripts/wiki_lint.py" "${PWD}/wiki"`. Add `--suggest-pages` if I asked for it. This catches orphans, broken wikilinks, oversized pages, missing frontmatter, stale pages, and duplicate slugs. 2b. If `wiki/graph/ontology.yaml` exists, also run `uv run --script "${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki/scripts/wiki_graph_lint.py" "${PWD}/wiki"`. Triage typed-edge findings (unknown predicates, missing evidence, broken object refs, alias collisions) the same way as structural ones — propose fixes, don't apply silently. After approved fixes, suggest running `uv run --script "${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki/scripts/wiki_graph_extract.py" "${PWD}/wiki"`. 3. Walk through the structural findings with me and propose a fix for each — don't apply fixes silently. Wait for my approval per item or in batch. 4. Run the semantic pass: read the most recently updated pages and the most-linked-to hubs (use `python "${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki/scripts/wiki_search.py" "" --wiki "${PWD}/wiki" --top-linked 10` to find them). Look for contradictions with older pages, unstated cross-references, and concepts mentioned in many pages but lacking their own page. 5. Surface gaps: topics I've expressed interest in but haven't ingested yet, claims that newer sources have superseded. 6. After applying approved fixes, update the index entries that changed and append one line to `log.md` summarizing the lint pass. 7. If the lint report is too long for me to triage comfortably, that's a signal the cadence is wrong (lint more often) or the schema needs revision — call it out.
Read more
description: Run a structural and semantic health check on the LLM Wiki. argument-hint: "[--suggest-pages]"
Run a lint pass on the wiki using the `llm-wiki` skill's lint workflow.
Arguments (if any): $ARGUMENTS
1. Read `wiki/SCHEMA.md` first if you haven't this session — it may declare additional lint rules. 2. Run the structural lint script: `python "${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki/scripts/wiki_lint.py" "${PWD}/wiki"`. Add `--suggest-pages` if I asked for it. This catches orphans, broken wikilinks, oversized pages, missing frontmatter, stale pages, and duplicate slugs. 2b. If `wiki/graph/ontology.yaml` exists, also run `uv run --script "${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki/scripts/wiki_graph_lint.py" "${PWD}/wiki"`. Triage typed-edge findings (unknown predicates, missing evidence, broken object refs, alias collisions) the same way as structural ones — propose fixes, don't apply silently. After approved fixes, suggest running `uv run --script "${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki/scripts/wiki_graph_extract.py" "${PWD}/wiki"`. 3. Walk through the structural findings with me and propose a fix for each — don't apply fixes silently. Wait for my approval per item or in batch. 4. Run the semantic pass: read the most recently updated pages and the most-linked-to hubs (use `python "${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki/scripts/wiki_search.py" "" --wiki "${PWD}/wiki" --top-linked 10` to find them). Look for contradictions with older pages, unstated cross-references, and concepts mentioned in many pages but lacking their own page. 5. Surface gaps: topics I've expressed interest in but haven't ingested yet, claims that newer sources have superseded. 6. After applying approved fixes, update the index entries that changed and append one line to `log.md` summarizing the lint pass. 7. If the lint report is too long for me to triage comfortably, that's a signal the cadence is wrong (lint more often) or the schema needs revision — call it out.
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.
Other commands on praneybehl-llm-wiki.
- /graph
Compile, lint, or query the wiki's typed graph layer.
Open command - /ingest
Ingest a source (paper, article, transcript, PDF, notes) into the LLM Wiki.
Open command - /init
Initialize a new LLM Wiki structure in this project (creates wiki/ and raw/ directories with templates).
Open command - /query
Query the LLM Wiki — answer a question from accumulated knowledge with citations.
Open command - /stats
Show wiki size, shape, and link density — and which scaling threshold the wiki is at.
Open command - /upgrade
Upgrade an existing LLM Wiki to the current plugin version (adds missing files idempotently; walks me through any SCHEMA.md merges by hand).
Open command