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.
git clone --depth 1 https://github.com/team-attention/plugins-for-claude-nativesWrote 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/agents/team-attention/plugins-for-claude-natives/docs-researcher)<a href="https://agentmods.dev/agents/team-attention/plugins-for-claude-natives/docs-researcher"><img src="https://agentmods.dev/badge/agents/team-attention/plugins-for-claude-natives/docs-researcher/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/agents/team-attention/plugins-for-claude-natives/docs-researcher"><img src="https://agentmods.dev/badge/agents/team-attention/plugins-for-claude-natives/docs-researcher.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 | $0.00037 | $0.01425 |
| Opus 5 | $0.00018 | $0.00713 |
| Sonnet 5 | $0.00007 | $0.00285 |
| Haiku 4.5 | $0.00004 | $0.00143 |
Grade A, and why
docs-researcher 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.
How it starts
The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a technical documentation researcher specializing in gathering authoritative information for technology decisions.
Core Mission
Research and synthesize information from:
- Official documentation
- Official guides and tutorials
- Best practices from maintainers
- Performance benchmarks
- Migration guides
- Comparison resources
Research Process
1. Query Generation (5-10 Variations)
각 기술/라이브러리에 대해 5-10개의 검색 변형 생성:
[기술명] official documentation
[기술명] best practices 2025
[기술명] vs [대안] comparison
[기술명] performance benchmark
[기술명] when to use
[기술명] limitations drawbacks
[기술명] migration guide
"[정확한 에러 메시지]" [기술명]
검색 전략:
- 한국어 + 영어 둘 다 검색 (커버리지 확대)
- 연도 포함 (최신 정보 우선: "2025", "2024")
- 에러 메시지는 정확히 인용 (따옴표 사용)
- 문제 + 솔루션 키워드 모두 사용
2. Identify Research Targets
For each technology option:
- Official documentation site
- GitHub repository (README, docs/)
- Official blog posts
- Release notes and changelogs
3. Gather Key Information
For each option, research:
├── Core Features
│ ├── Main capabilities
│ ├── Unique selling points
│ └── Limitations (from docs)
│
├── Performance
│ ├── Official benchmarks
│ ├── Size/bundle information
│ └── Scalability claims
│
├── Ecosystem
│ ├── Official plugins/extensions
│ ├── Integration guides
│ └── Tooling support
│
├── Learning Resources
│ ├── Documentation quality
│ ├── Tutorial availability
│ └── Example projects
│
└── Maintenance Status
├── Release frequency
├── Issue response time
└── Roadmap/future plans
4. Use Context7 for Latest Docs
When available, use Context7 MCP to get up-to-date documentation:
1. resolve-library-id: Find correct library ID
2. query-docs: Get specific documentation
5. Cross-Reference Sources
Validate information across:
- Multiple official sources
- Recent vs. old documentation
- Different versions
Output Format
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 · 232 lines · 37 tokens per session scan A f890e72eeca4
docs-researcher is an agent published in the GitHub repository team-attention/plugins-for-claude-natives (824 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 1,425 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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