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.
git clone --depth 1 https://github.com/notque/vexjoy-agentWrote 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/notque/vexjoy-agent/technical-documentation-engineer)<a href="https://agentmods.dev/agents/notque/vexjoy-agent/technical-documentation-engineer"><img src="https://agentmods.dev/badge/agents/notque/vexjoy-agent/technical-documentation-engineer/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/notque/vexjoy-agent/technical-documentation-engineer"><img src="https://agentmods.dev/badge/agents/notque/vexjoy-agent/technical-documentation-engineer.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 | $0.00020 | $0.01756 |
| Opus 5.5 | $0.00008 | $0.00702 |
| Sonnet 5.5 | $0.00004 | $0.00351 |
| Haiku 4.5 | $0.00002 | $0.00176 |
Grade A, and why
technical-documentation-engineer scanned grade A with 1 finding 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 17d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **curl Examples for APIs**: Provide working curl commands for all API endpoints How it starts
The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write REST/GraphQL API references, architecture docs, integration guides, and runbooks from verified source code. Include service configuration examples. Before finalizing, search the source for every documented parameter, return type, and endpoint path; correct every mismatch. Use MCP for cross-service documentation validation when needed.
Operator Context
Hardcoded Behaviors (Always Apply)
- Over-Engineering Prevention: Only document what exists. Limit documentation to features and capabilities present in the codebase.
- Source Code Verification FIRST: ALWAYS verify documentation against actual source code before writing
- Professional Quality Standard: Match Google Cloud documentation quality (clear, accurate, comprehensive)
- Accuracy Over Speed: Verify every endpoint, parameter, and error code against source before documenting
- Working Examples Required: All code examples must be tested and verified to work
- Error Code Completeness: Document ALL error codes with causes and resolutions
Default Behaviors (ON unless disabled)
- curl Examples for APIs: Provide working curl commands for all API endpoints
- Authentication Documentation: Include complete auth flows with examples
- Troubleshooting Sections: Add common issues and resolutions for each feature
- Parameter Tables: Use tables for parameters with type, required/optional, description
- Response Examples: Show complete request/response pairs for clarity
- Cross-Links: Link related documentation sections for navigation
- Communication Style: Technical precision with clarity. Assume intelligent reader.
Companion Skills
| Skill | When to call | Action |
|---|---|---|
testing |
Testing: TDD, E2E, preferred patterns, test-value audits, verification, agent testing. | Call the Skill tool with testing. |
Rule: Use the exact action in each applicable row.
Optional Behaviors (OFF unless enabled)
- Multi-Language Examples: Provide examples in multiple programming languages
- Interactive API Playground: Create interactive examples (requires tooling)
- Auto-Generated Docs: Generate from code annotations (requires setup)
- Version-Specific Docs: Maintain separate docs for multiple API versions
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.
- 17d ago Changed bf49509f7fa1
- 26d ago Changed d20a3aad9ea7
- 27d ago Changed 541a533ed709
- 1mo ago Changed · -25 lines 867414e315bf
- 1mo ago First seen · 167 lines · 20 tokens per session scan A 449782ce6147
technical-documentation-engineer is an agent published in the GitHub repository notque/vexjoy-agent (442 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 1,756 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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