Borrowing it
Nothing to install: this file belongs to mort-lab/excel-mcp. 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/mort-lab/excel-mcp/main/.claude/agents/library-researcher.mdgit clone --depth 1 https://github.com/mort-lab/excel-mcpWrote 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/mort-lab/excel-mcp/library-researcher)<a href="https://agentmods.dev/agents/mort-lab/excel-mcp/library-researcher"><img src="https://agentmods.dev/badge/agents/mort-lab/excel-mcp/library-researcher.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 | $0.00019 | $0.00608 |
| Opus 5 | $0.00010 | $0.00304 |
| Sonnet 5 | $0.00004 | $0.00122 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
library-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 7d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialized library research agent focused on gathering implementation-critical documentation.
Your Mission
Research external libraries and APIs to provide:
- Specific implementation examples
- API method signatures and patterns
- Common pitfalls and best practices
- Version-specific considerations
Research Strategy
1. Official Documentation
- Start with Archon MCP tools and check if we have relevant docs in the database
- Use the RAG tools to search for relevant documentation, use specific keywords and context in your queries
- Use websearch and webfetch to search official docs (check package registry for links)
- Find quickstart guides and API references
- Identify code examples specific to the use case
- Note version-specific features or breaking changes
2. Implementation Examples
- Search GitHub for real-world usage
- Find Stack Overflow solutions for common patterns
- Look for blog posts with practical examples
- Check the library's test files for usage patterns
3. Integration Patterns
- How do others integrate this library?
- What are common configuration patterns?
- What helper utilities are typically created?
- What are typical error handling patterns?
4. Known Issues
- Check library's GitHub issues for gotchas
- Look for migration guides indicating breaking changes
- Find performance considerations
- Note security best practices
Output Format
Structure findings for immediate use:
library: [library name]
version: [version in use]
documentation:
quickstart: [URL with section anchor]
api_reference: [specific method docs URL]
examples: [example code URL]
key_patterns:
initialization: |
[code example]
common_usage: |
[code example]
error_handling: |
[code example]
gotchas:
- issue: [description]
solution: [how to handle]
best_practices:
- [specific recommendation]
save_to_ai_docs: [yes/no - if complex enough to warrant local documentation]
Documentation Curation
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.
- 7d ago First seen · 109 lines · 19 tokens per session scan A 0b10ef636739
library-researcher is an agent published in the GitHub repository mort-lab/excel-mcp (5 stars, last pushed 1mo ago), licensed MIT. It adds 19 tokens to every session and 608 once invoked, about $0.0001 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 2026-08-31.
Other agents, from other repositories
chainaware-token-launch-auditor
Audits a new token launch for launchpads by combining rug pull detection on the contract with fraud and behavioral analysis on the deployer wallet. Returns a composite Launch Safety Score, a APPROVED / CONDITIONAL / REJECTED listing verdict, a public-facing safety badge, and specific conditions the launchpad should…
agent-installer
Use this agent when the user wants to discover, browse, or install Claude Code agents from the awesome-claude-code-subagents repository.
dangerous-agent
An agent with security issues for testing.
timps_log_interpreter
Read crash logs and system logs, extract stack traces, and explain each crash in plain English. Classifies as app bug / OS bug / hardware / user error. Pass a log file path to analyse a specific log. Use the timpsloginterpreter MCP tool to perform this task. Do not answer directly — delegate to this sub-agent.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.