Borrowing it
Nothing to install: this file belongs to irahardianto/qurio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/irahardianto/qurio/main/.gemini/skills/knowledge-searching/SKILL.mdgit clone --depth 1 https://github.com/irahardianto/qurioWrote 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/irahardianto/qurio/knowledge-searching)<a href="https://agentmods.dev/skills/irahardianto/qurio/knowledge-searching"><img src="https://agentmods.dev/badge/skills/irahardianto/qurio/knowledge-searching/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/irahardianto/qurio/knowledge-searching"><img src="https://agentmods.dev/badge/skills/irahardianto/qurio/knowledge-searching.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00056 | $0.00390 |
| Opus 5 | $0.00028 | $0.00195 |
| Sonnet 5 | $0.00011 | $0.00078 |
| Haiku 4.5 | $0.00006 | $0.00039 |
Grade A, and why
knowledge-searching 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 10d 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
Knowledge Searching
Overview
Retrieves implementation knowledge to inform decision-making across the software development lifecycle.
Use this skill when you need:
- Implementation details for specific libraries/frameworks
- Code examples for patterns or features
- Documentation references libraries/frameworks usage
Announce at start: "I'm using the knowledge-research skill to gather implementation details."
Core Functions
Searching Specific Documentation:
- Get sources →
rag_get_available_sources()- Returns list with id, title, url - Find source ID → Match to documentation (e.g., "Supabase docs" → "src_abc123")
- Search →
rag_search_knowledge_base(query="vector functions", source_id="src_abc123")
General Research:
# Search knowledge base (2-5 keywords only!)
rag_search_knowledge_base(query="authentication JWT", match_count=5)
# Find code examples
rag_search_code_examples(query="React hooks", match_count=3)
Query Guidelines
✅ Good Queries (2-5 keywords)
"authentication JWT""vector functions""React hooks""Go context timeout""SQL row level security"
❌ Bad Queries (too long/verbose)
"How do I implement JWT authentication in Go?""What are the best practices for vector similarity search?""Show me examples of React hooks for state management"
Rule: Keep queries SHORT and keyword-focused for optimal search results.
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.
- 10d ago First seen · 49 lines · 56 tokens per session scan A 576f611ae415
knowledge-searching is a skill published in the GitHub repository irahardianto/qurio (17 stars, last pushed 6mo ago), licensed MIT. It adds 56 tokens to every session and 390 once invoked, about $0.0003 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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