Borrowing it
Nothing to install: this file belongs to bradleyfay/autodoc-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/bradleyfay/autodoc-mcp/main/.claude/agents/README.mdgit clone --depth 1 https://github.com/bradleyfay/autodoc-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/bradleyfay/autodoc-mcp/readme)<a href="https://agentmods.dev/agents/bradleyfay/autodoc-mcp/readme"><img src="https://agentmods.dev/badge/agents/bradleyfay/autodoc-mcp/readme.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 | $0.00000 | $0.00615 |
| Opus 5 | $0.00000 | $0.00308 |
| Sonnet 5 | $0.00000 | $0.00123 |
| Haiku 4.5 | $0.00000 | $0.00061 |
Grade A, and why
README 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 6d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude Code Agent Specifications
This directory contains fully-implemented agent specifications for the AutoDocs MCP Server project. Each agent is a specialized AI assistant designed to work within Claude Code's multi-agent ecosystem.
Available Agents
🎯 Project Management & Planning
- project-planning-steward: Project organization expert for creating and maintaining comprehensive project documentation, scope definition, and status tracking within the planning folder structure
🏗️ Architecture & Design
- agent-design-architect: Meta-agent specialist in designing, analyzing, and optimizing multi-agent systems, agent collaboration patterns, and system architecture
⚙️ Core Development
- core-services: Expert in core business logic, dependency resolution, documentation processing, and performance optimization for the AutoDocs MCP Server
- mcp-protocol: Specialist in MCP protocol implementation, tool definitions, server development, and client integrations
📚 Documentation & Content
- docs-integration: Expert in technical documentation, API documentation, integration guides, and user onboarding materials
- technical-writer: Specialist in the Diátaxis documentation framework for user-centered documentation design and content strategy
🧪 Testing & Quality
- testing-specialist: Expert in comprehensive testing strategies, pytest ecosystem, test automation, and quality assurance
🚀 Operations & Product
- production-ops: Expert in deployment, monitoring, configuration, security, and production readiness
- product-manager: Expert in product strategy, roadmap prioritization, requirements analysis, and stakeholder coordination
🔗 Workflow Coordination (Advanced)
- workflow-orchestrator: Meta-cognitive agent for task decomposition and multi-agent workflow coordination
- context-coordinator: Expert in hierarchical context management and intelligent context sharing across workflows
Agent File 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.
- 6d ago First seen · 69 lines · 0 tokens per session scan A 8eb7abee8af8
README is an agent published in the GitHub repository bradleyfay/autodoc-mcp (1 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 615 tokens. 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
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.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.