Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add eliransu/digital-brain --skill wiki-querygit clone --depth 1 https://github.com/eliransu/digital-brainWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/eliransu/digital-brain/wiki-query)<a href="https://agentmods.dev/skills/eliransu/digital-brain/wiki-query"><img src="https://agentmods.dev/badge/skills/eliransu/digital-brain/wiki-query.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00089 | $0.01257 |
| Opus 5 | $0.00044 | $0.00629 |
| Sonnet 5 | $0.00018 | $0.00251 |
| Haiku 4.5 | $0.00009 | $0.00126 |
Grade A, and why
wiki-query scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
97% identical to wiki-query — 33 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
wiki-query: Query the Wiki
The wiki has already done the synthesis work. Read strategically, answer precisely, and file good answers back so the knowledge compounds.
Query Modes
Three depths. Choose based on the question complexity.
| Mode | Trigger | Reads | Token cost | Best for |
|---|---|---|---|---|
| Quick | query quick: ... or simple factual Q |
hot.md + index.md only | ~1,500 | "What is X?", date lookups, quick facts |
| Standard | default (no flag) | hot.md + index + 3-5 pages | ~3,000 | Most questions |
| Deep | query deep: ... or "thorough", "comprehensive" |
Full wiki + optional web | ~8,000+ | "Compare A vs B across everything", synthesis, gap analysis |
Quick Mode
Use when the answer is likely in the hot cache or index summary.
- Read
wiki/hot.md. If it answers the question, respond immediately. - If not, read
wiki/index.md. Scan descriptions for the answer. - If found in index summary, respond and do not open any pages.
- If not found, say "Not in quick cache. Run as standard query?"
Do not open individual wiki pages in quick mode.
Standard Query Workflow
- Read
wiki/hot.mdfirst. It may already have the answer or directly relevant context. - Read
wiki/index.mdto find the most relevant pages (scan for titles and descriptions). - Read those pages. Follow wikilinks to depth-2 for key entities. No deeper.
- Synthesize the answer in chat. Cite sources with wikilinks:
(Source: [[Page Name]]). - Offer to file the answer: "This analysis seems worth keeping. Should I save it as
wiki/synthesis/answer-name.md?" - If the question reveals a gap: say "I don't have enough on X. Want to find a source?"
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 174 lines · 89 tokens per session scan A 333907d615ce
wiki-query is a skill published in the GitHub repository eliransu/digital-brain (1 stars, last pushed 3mo ago), licensed MIT. It adds 89 tokens to every session and 1,257 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to wiki-query, differing in 33 lines, and is treated as a copy.
Other skills, from other repositories
llm-wiki
Build and maintain an LLM-curated personal knowledge base — the "LLM Wiki" pattern from Andrej Karpathy's April 2026 gist. Use this skill whenever the user wants to ingest a source (paper, article, transcript, PDF, notes) into a persistent compounding knowledge base, ask a question against accumulated notes, lint or…
llm-wiki
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karpathy-llm-wiki
Use when building or maintaining a personal LLM-powered knowledge base. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki quality, 'add to wiki', 'what do I know about', or any mention of 'LLM wiki' or 'Karpathy wiki'.
mindbase
Maintain a persistent AI-tended research wiki. Activates when the user wants to ingest a source (PDF, URL, article, paste), capture a thought, build the wiki context, query what's already known, lint for orphans/contradictions, or maintain page conventions. Phrases include "add this to my wiki", "today I decided…"…
migrate
Scan the project and migrate existing documentation into OKF format. Use when the user wants to populate the knowledge base from existing docs, README, schemas, API specs, runbooks, or any structured project knowledge. Trigger on "migrate to okf", "populate the knowledge base", "scan my docs", "convert docs to okf"…
ingest
Create or update a single OKF concept file from raw input. Use when the user wants to document a specific table, metric, API, service, or concept in the knowledge base — even if they say "add this to the okf", "documenta essa tabela", "cria um conceito pra isso", "adiciona no knowledge base", "register this API", or…