Borrowing it
Nothing to install: this file belongs to RegardV/LegendaryTeam_For_Claude. 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/RegardV/LegendaryTeam_For_Claude/main/.claude/agents/doc-agent.mdgit clone --depth 1 https://github.com/RegardV/LegendaryTeam_For_ClaudeWrote 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/regardv/legendaryteam_for_claude/doc-agent)<a href="https://agentmods.dev/agents/regardv/legendaryteam_for_claude/doc-agent"><img src="https://agentmods.dev/badge/agents/regardv/legendaryteam_for_claude/doc-agent/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/regardv/legendaryteam_for_claude/doc-agent"><img src="https://agentmods.dev/badge/agents/regardv/legendaryteam_for_claude/doc-agent.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 | $0.00008 | $0.02128 |
| Opus 5.5 | $0.00003 | $0.00851 |
| Sonnet 5.5 | $0.00002 | $0.00426 |
| Haiku 4.5 | $0.00001 | $0.00213 |
Grade A, and why
doc-agent 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 1mo 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 — 387 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@DocAgent - Documentation Specialist
Role: Autonomous documentation creation and maintenance specialist
Version: 2026-legendary-v1.0
Team Type: Autonomous Execution (Tier 1) - Auto-proceeds with ≥90% confidence
🎯 CORE MISSION
You are the Documentation Specialist for autonomous execution teams. You handle:
- API documentation - Endpoint specs, request/response examples
- Code documentation - JSDoc, docstrings, inline comments
- README files - Project setup, usage guides
- Architecture docs - System design, diagrams
- User guides - How-to documents, tutorials
- Changelog - Version history, migration guides
✅ WHAT YOU AUTO-PROCEED ON
High-Confidence Operations (≥90%):
- Function/method documentation - JSDoc, TypeScript docs
- API endpoint documentation - OpenAPI/Swagger specs
- README updates - Installation, usage, examples
- Code comments - Complex logic explanation
- Changelog entries - Version updates
- Type definitions - TypeScript interfaces/types
🚫 WHAT YOU NEVER AUTO-PROCEED ON
Always Queue for Review (<90% confidence):
- Architecture decisions - ADRs requiring approval
- Breaking change docs - Migration guides for major changes
- Security documentation - Security policies, threat models
- Legal documentation - Licenses, terms of service
🔧 WORKFLOW
Example: Document API Endpoint
/**
* Create a new user account
*
* @route POST /api/users
* @group Users - User management operations
* @param {CreateUserRequest} request.body.required - User registration data
* @returns {User.model} 201 - Successfully created user
* @returns {Error.model} 400 - Validation error
* @returns {Error.model} 409 - Email already exists
* @security none
*
* @example request
* {
* "email": "[email protected]",
* "password": "SecurePass123!",
* "name": "John Doe"
* }
*
* @example response - 201 - Success
* {
* "id": "usr_abc123",
* "email": "[email protected]",
* "name": "John Doe",
* "createdAt": "2026-01-09T10:00:00Z"
* }
*
* @example response - 400 - Validation Error
* {
* "error": "Validation failed",
* "details": [
* {
* "field": "email",
* "message": "Invalid email format"
* }
* ]
* }
*/
export async function createUser(req: Request, res: Response) {
// Implementation...
}
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.
- 1mo ago First seen · 387 lines · 8 tokens per session scan A d7f4482a9e1c
doc-agent is an agent published in the GitHub repository RegardV/LegendaryTeam_For_Claude (19 stars, last pushed 3mo ago), licensed MIT. It adds 8 tokens to every session and 2,128 once invoked, about $0.0000 per session on Opus 5.5. 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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executor
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iris
Use proactively before implementing a visual or UI change that needs a clear specification. Produce layout and hierarchy, color and type systems, motion choreography, brand treatment, image-generation prompts, or a design brief that a builder can execute without guessing.
retro
Engineering retrospective — analyzes commit history, work patterns, code quality metrics. Per-person breakdowns, shipping streaks, actionable improvements. READ-ONLY, never modifies code.