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 agentmods add skills/open-gitagent/opengap/wiki-querynpx skills add open-gitagent/opengap --skill wiki-querygit clone --depth 1 https://github.com/open-gitagent/opengapWhat 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 | $0.00043 | $0.00436 |
| Opus 5 | $0.00022 | $0.00218 |
| Sonnet 5 | $0.00009 | $0.00087 |
| Haiku 4.5 | $0.00004 | $0.00044 |
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 3d 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.
What it actually says
Wiki Query
Answer questions by searching and synthesizing from the wiki.
Workflow
Step 1: Search the wiki
- Read
memory/wiki/index.mdto find relevant pages - Use Grep to search for specific terms across
memory/wiki/ - Read the most relevant pages (usually 3-10)
Step 2: Synthesize an answer
- Combine information from multiple wiki pages
- Cite sources: reference both wiki pages and the underlying raw documents
- Note confidence level — distinguish well-sourced claims from inferences
- Flag if the wiki has gaps on this topic
Step 3: Present the answer
Format depends on the question:
- Factual question — direct answer with citations
- Comparison — markdown table comparing entities/concepts
- Overview — structured summary with sections
- Analysis — synthesis with explicit reasoning chain
Step 4: File back (if valuable)
If the answer represents a useful synthesis that doesn't exist as a wiki page:
- Ask the user: "This answer synthesizes information that isn't captured in the wiki yet. Should I file it as a new page?"
- If yes: create a new wiki page in
memory/wiki/ - Update
memory/wiki/index.md - Append to
memory/log.md:## [YYYY-MM-DD] query-filed | Page Title - Question: [original question] - Pages referenced: [list] - New page: memory/wiki/page-name.md
Key Insight
Good answers should not disappear into chat history. A comparison you asked for, an analysis, a connection you discovered — these are valuable wiki content. Filing them back means your explorations compound in the knowledge base just like ingested sources do.
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.
- 3d ago First seen · 47 lines · 43 tokens per session scan A a36232a746c2
wiki-query is a skill published in the GitHub repository open-gitagent/opengap (2,921 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 436 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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