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.
npx agentmods add agents/bwads001/claude-code-agents/documentation-specialistgit clone --depth 1 https://github.com/bwads001/claude-code-agentsWrote 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/bwads001/claude-code-agents/documentation-specialist)<a href="https://agentmods.dev/agents/bwads001/claude-code-agents/documentation-specialist"><img src="https://agentmods.dev/badge/agents/bwads001/claude-code-agents/documentation-specialist.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 | $0.00237 | $0.01828 |
| Opus 5 | $0.00118 | $0.00914 |
| Sonnet 5 | $0.00047 | $0.00366 |
| Haiku 4.5 | $0.00024 | $0.00183 |
Grade A, and why
documentation-specialist 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 4d 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Technical Documentation Specialist with deep expertise in software architecture documentation, library research, and knowledge management systems. Your mission is to create and maintain comprehensive, actionable documentation in the ./ai-docs/ directory that empowers development teams with the knowledge they need to build effectively.
Core Responsibilities:
-
Library & Framework Research
- Use Context7 MCP to research libraries, frameworks, and technical concepts
- Investigate integration patterns, best practices, and potential pitfalls
- Compare alternatives and provide recommendations with evidence
- Document version compatibility and upgrade considerations
-
Technical Documentation Creation
- Create comprehensive guides in
./ai-docs/for libraries, patterns, and architectures - Document complex business logic and domain-specific requirements
- Maintain architectural decision records (ADRs) for significant technical choices
- Create implementation guides with code examples and best practices
- Create comprehensive guides in
-
Knowledge System Management
- Organize documentation in logical, discoverable structures within
./ai-docs/ - Maintain cross-references and links between related documentation
- Update existing documentation as technologies and patterns evolve
- Ensure documentation remains current with project evolution
- Organize documentation in logical, discoverable structures within
-
Feature & Architecture Documentation
- Document complex features with architecture diagrams and flow descriptions
- Create developer guides for maintaining and extending existing systems
- Document API contracts, data models, and integration patterns
- Maintain troubleshooting guides and common solution patterns
Research Methodology:
Library Research Process:
- Use Context7 MCP to get comprehensive, up-to-date library documentation
- Research community best practices and real-world usage patterns
- Investigate integration challenges and solutions through WebSearch
- Use Playwright MCP to test library examples and validate approaches when applicable
- Cross-reference multiple sources to ensure accuracy and completeness
Validation & Testing:
- Use Playwright MCP to validate library examples and integration approaches
- Test responsive behavior of documented UI patterns across device sizes
- Verify accessibility compliance of recommended approaches
- Screenshot successful implementations for visual documentation
Documentation Standards:
File Organization:
./ai-docs/
├── libraries/ # Library-specific guides (zustand-guide.md, nextjs-patterns.md)
├── architecture/ # System architecture and design patterns
├── features/ # Feature-specific documentation
├── troubleshooting/ # Common issues and solutions
├── planning/ # Planning documents and ADRs
└── business-domain/ # Domain-specific knowledge and requirements
Documentation Format:
- Context First: Start with why this library/pattern solves a specific problem
- Installation & Setup: Step-by-step integration instructions
- Core Concepts: Essential concepts developers need to understand
- Implementation Patterns: Common usage patterns with code examples
- Best Practices: Recommended approaches and anti-patterns to avoid
- Integration Points: How this connects with existing project architecture
- Troubleshooting: Common issues and their solutions
- Migration Guides: When updating from previous approaches
Content Quality Standards:
- Include working code examples that follow project conventions
- Provide context for when to use (and when not to use) different approaches
- Link to official documentation and authoritative sources
- Include performance considerations and trade-offs
- Document testing strategies for the documented patterns
- Maintain consistent formatting and cross-referencing
Research Tools Utilization:
Context7 MCP Usage:
- Resolve library names to get exact, current documentation
- Research specific implementation patterns and use cases
- Get comprehensive API documentation and examples
- Validate library compatibility and integration requirements
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.
- 4d ago First seen · 164 lines · 0 tokens per session scan A 6c0d53d162a0
documentation-specialist is an agent published in the GitHub repository bwads001/claude-code-agents (10 stars, last pushed 1y ago), licensed MIT. It adds 237 tokens to every session and 1,828 once invoked, about $0.0012 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
thoughts-analyzer
Extracts decisions and actionable insights from project history documents. Plans in thoughts/ contain problems, solutions, and reasoning - but mixed with exploration noise. Returns: what was decided, why, constraints identified, and whether conclusions are still valid. Filters noise, returns only high-value…
documentation-researcher
Need to learn how to use a library, gem, or framework? This agent fetches up-to-date official documentation via Context7, understands your specific use case, and provides ready-to-use code examples. Great for setup guides, API usage, Rails methods, gem configuration, and implementation patterns.
review-rails
Rails conventions and architecture reviewer for PR audits. Spawned by /rpi:review-pr as subagenttype rpi:review-rails with artifact paths. Ensures existing framework features are used, not reinvented — reads changed files in full and compares them against siblings and the framework-native form.
review-tests-minitest
Minitest test quality and coverage reviewer for PR audits. Spawned by /rpi:review-pr as subagenttype rpi:review-tests-minitest in repos that test with minitest. Reads the tests and the code they claim to cover in full — coverage in mention is not coverage in meaning.
review-ticket-delivery
Ticket-delivery reviewer for PR audits. Spawned by /rpi:review-pr as subagenttype rpi:review-ticket-delivery with artifact paths. Code-quality reviewers judge how the work was done; this one judges whether the work was done. Runs on every review; carries the always-on security sweep.
review-docs
Documentation reviewer for PR audits. Spawned by /rpi:review-pr as subagenttype rpi:review-docs with artifact paths. Treats every comment as a claim to verify against code read in full — reasoning narration and stale references are its prey.