cs-wiki-librarian
Dispatched sub-agent that answers queries against an LLM Wiki vault. Reads index.md first, drills into 3-10 relevant pages across categories, synthesizes an answer with inline [[wikilink]] citations, and offers to file the answer back into the wiki as a new comparison or synthesis page. Spawn when the user asks a substantive question the wiki might answer, says "what does the wiki say about X", "compare A and B across my sources", or wants to explore a topic.
Best use case
cs-wiki-librarian is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Dispatched sub-agent that answers queries against an LLM Wiki vault. Reads index.md first, drills into 3-10 relevant pages across categories, synthesizes an answer with inline [[wikilink]] citations, and offers to file the answer back into the wiki as a new comparison or synthesis page. Spawn when the user asks a substantive question the wiki might answer, says "what does the wiki say about X", "compare A and B across my sources", or wants to explore a topic.
Teams using cs-wiki-librarian 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/cs-wiki-librarian/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cs-wiki-librarian Compares
| Feature / Agent | cs-wiki-librarian | 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?
Dispatched sub-agent that answers queries against an LLM Wiki vault. Reads index.md first, drills into 3-10 relevant pages across categories, synthesizes an answer with inline [[wikilink]] citations, and offers to file the answer back into the wiki as a new comparison or synthesis page. Spawn when the user asks a substantive question the wiki might answer, says "what does the wiki say about X", "compare A and B across my sources", or wants to explore a topic.
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.
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SKILL.md Source
# wiki-librarian ## Role You answer questions against an LLM Wiki vault. You prioritize reading over re-deriving — the wiki already contains pre-synthesized knowledge with cross-references and citations. Your job is to find the right pages, read them, and compose an answer that cites them properly. You also **file good answers back** into the wiki so explorations compound. You are spawned **per-query**, not as a long-running agent. ## Inputs - The user's question - The current state of `wiki/` (especially `index.md`) ## Workflow Follow `references/query-workflow.md`. Summary: ### 1. Read `index.md` first The index is the catalog. Scan it and pick the 3-10 pages most likely to contain the answer. Pick across categories: - `synthesis/` for the big picture - `concepts/` for definitions - `sources/` for evidence - `entities/` for context - `comparisons/` for explicit contrasts ### 2. Read the picked pages in full They're short and curated. The wiki has done the hard work. ### 3. Follow wikilinks opportunistically If a read page points to another clearly relevant page, follow it. Stop when you have enough. ### 4. Fall back to search if needed If the index doesn't surface the right pages, run: ```bash python <plugin>/scripts/wiki_search.py --vault . --query "<terms>" --limit 5 ``` Flag this to the user — stale index means lint time. ### 5. Synthesize the answer Format: - **Direct answer** — 1-3 sentences - **Supporting detail** — organized thematically - **Inline citations** — `[[sources/xxx]]` wikilinks throughout; every claim links to its source - **Related pages** — 3-5 wikilinks at the end ### 6. Offer to file the answer back This is the compounding move. At the end of the answer, ask: > _Should I file this as a new page in the wiki? Suggested location: > `wiki/comparisons/<slug>.md` — or I can append it to an existing page._ If yes: - Pick the right category (most often `comparisons/` or `synthesis/`) - Use the appropriate template (see llm-wiki skill's `references/page-formats.md`) - Add frontmatter with `category`, `summary`, `sources` (count), `updated` - Update `wiki/index.md` (inline or via script) - Append to `log.md`: `python <plugin>/scripts/append_log.py --vault . --op create --title "<question>" --detail "filed query response to <path>"` ## Rules - **Read the index first.** Do not grep the entire wiki on every query. - **Every claim cites a page.** No uncited assertions. - **If the wiki doesn't know, say so.** Suggest a source to ingest instead of inventing content. - **Offer to file back** every substantive answer — but don't file trivial one-off answers. - **Output format follows the question.** Comparison questions get tables. Overview questions get markdown pages. Data questions get charts (save to `wiki/assets/charts/`). ## Red flags - Answering without reading the index → go back - Citing only one source for a multi-source question → broaden - Inventing concepts not in the wiki → stop and suggest ingestion - Creating a new page for a trivial question → don't pollute the wiki
Related Skills
wiki-query
Query the LLM Wiki — reads index.md first, drills into 3-10 relevant pages, synthesizes an answer with inline [[wikilink]] citations, and offers to file the answer back as a new comparison or synthesis page. Usage /wiki-query "<question>"
wiki-log
Show recent entries from the LLM Wiki log (wiki/log.md). Uses the standardized
wiki-lint
Run a health check on the LLM Wiki vault — mechanical checks (orphans, broken links, stale pages, missing frontmatter, log gap, duplicates) plus semantic checks (contradictions, cross-reference gaps, concepts missing their own page). Outputs a markdown report with suggested actions. Usage /wiki-lint [--stale-days N] [--log-gap-days N]
wiki-init
Bootstrap a fresh LLM Wiki vault with the three-layer structure, schema files, and starter templates. Usage /wiki-init <path> --topic "<topic>" [--tool all|claude-code|codex|cursor|antigravity]
wiki-ingest
Ingest a source file from raw/ into the LLM Wiki — read, discuss, write summary page, update cross-references across 5-15 pages, regenerate index, append to log. Usage /wiki-ingest <path-to-source>
llm-wiki
Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
cs-wiki-linter
Dispatched sub-agent that runs a periodic health check on an LLM Wiki vault. Runs mechanical checks via scripts (orphans, broken links, stale pages, missing frontmatter, duplicate titles, log gaps), does semantic checks (contradictions, stale claims, cross-reference gaps, concepts missing their own page), and produces a markdown report with suggested actions. Spawn weekly, after batch ingests, or when the user says "check the wiki" / "lint my wiki" / "audit the vault".
cs-wiki-ingestor
Dispatched sub-agent that ingests a new source into an LLM Wiki vault. Reads the source, proposes TL;DR and key claims, identifies which entity/concept/synthesis pages will be touched, flags contradictions with existing pages, and — after user confirmation — writes the source summary, updates cross-references across 5-15 pages, regenerates the index, and appends a standardized log entry. Spawn when the user says "ingest this", "add this paper/article/book to the wiki", or drops a file into raw/.
tc
Track technical changes with structured records, a state machine, and session handoff. Usage: /tc <init|create|update|status|resume|close|export|dashboard> [args]
tc-tracker
Use when the user asks to track technical changes, create change records, manage TC lifecycles, or hand off work between AI sessions. Covers init/create/update/status/resume/close/export workflows for structured code change documentation.
karpathy-coder
Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on "review my diff", "check complexity", "am I overcomplicating this", "karpathy check", "before I commit", or any code quality concern where the LLM might be overcoding.
karpathy-check
Run Karpathy's 4-principle review on staged changes or the last commit. Checks complexity, diff noise, hidden assumptions, and goal verification. Usage /karpathy-check [--last-commit]