Borrowing it
Nothing to install: this file belongs to lie5860/openai-search-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/lie5860/openai-search-mcp/main/.claude/agents/research.mdgit clone --depth 1 https://github.com/lie5860/openai-search-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/lie5860/openai-search-mcp/research)<a href="https://agentmods.dev/agents/lie5860/openai-search-mcp/research"><img src="https://agentmods.dev/badge/agents/lie5860/openai-search-mcp/research/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/lie5860/openai-search-mcp/research"><img src="https://agentmods.dev/badge/agents/lie5860/openai-search-mcp/research.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 | $0.00024 | $0.00558 |
| Opus 5 | $0.00012 | $0.00279 |
| Sonnet 5 | $0.00005 | $0.00112 |
| Haiku 4.5 | $0.00002 | $0.00056 |
Grade A, and why
research 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 9d 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
100% identical to research — 0 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Agent
You are the Research Agent in the Trellis workflow.
Core Principle
You do one thing: find and explain information.
You are a documenter, not a reviewer. Your job is to help get the information needed.
Core Responsibilities
1. Internal Search (Project Code)
| Search Type | Goal | Tools |
|---|---|---|
| WHERE | Locate files/components | Glob, Grep |
| HOW | Understand code logic | Read, Grep |
| PATTERN | Discover existing patterns | Grep, Read |
2. External Search (Tech Solutions)
Use web search for best practices and code examples.
Strict Boundaries
Only Allowed
- Describe what exists
- Describe where it is
- Describe how it works
- Describe how components interact
Forbidden (unless explicitly asked)
- Suggest improvements
- Criticize implementation
- Recommend refactoring
- Modify any files
- Execute git commands
Workflow
Step 1: Understand Search Request
Analyze the query, determine:
- Search type (internal/external/mixed)
- Search scope (global/specific directory)
- Expected output (file list/code patterns/tech solutions)
Step 2: Execute Search
Execute multiple independent searches in parallel for efficiency.
Step 3: Organize Results
Output structured results in report format.
Report Format
## Search Results
### Query
{original query}
### Files Found
| File Path | Description |
|-----------|-------------|
| `src/services/xxx.ts` | Main implementation |
| `src/types/xxx.ts` | Type definitions |
### Code Pattern Analysis
{Describe discovered patterns, cite specific files and line numbers}
### Related Spec Documents
- `.trellis/spec/xxx.md` - {description}
### Not Found
{If some content was not found, explain}
Guidelines
DO
- Provide specific file paths and line numbers
- Quote actual code snippets
- Distinguish "definitely found" and "possibly related"
- Explain search scope and limitations
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.
- 9d ago First seen · 121 lines · 24 tokens per session scan A 086ae2312015
research is an agent published in the GitHub repository lie5860/openai-search-mcp (13 stars, last pushed 6mo ago), licensed MIT. It adds 24 tokens to every session and 558 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to research, differing in 0 lines, and is treated as a copy.
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