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 skills add jjmartres/ai-coding-agents --skill document-codegit clone --depth 1 https://github.com/jjmartres/ai-coding-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/skills/jjmartres/ai-coding-agents/document-code)<a href="https://agentmods.dev/skills/jjmartres/ai-coding-agents/document-code"><img src="https://agentmods.dev/badge/skills/jjmartres/ai-coding-agents/document-code/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/skills/jjmartres/ai-coding-agents/document-code"><img src="https://agentmods.dev/badge/skills/jjmartres/ai-coding-agents/document-code.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 | $0.00088 | $0.02530 |
| Opus 5.5 | $0.00035 | $0.01012 |
| Sonnet 5.5 | $0.00018 | $0.00506 |
| Haiku 4.5 | $0.00009 | $0.00253 |
Grade A, and why
document-code 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 20d 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 — 398 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Documentation Standards
Apply Google Style documentation standards to Python (docstrings), Go (comments), TypeScript (JSDoc), and Terraform (descriptions). Ensures consistent, professional, and comprehensive code documentation across multiple languages.
When to Apply This Skill
Use this skill when:
- Writing new functions, classes, or packages
- Reviewing code for documentation quality
- User requests "document this code" or "add docstrings"
- User mentions "Google Style" or documentation standards
- Refactoring code that lacks proper documentation
- Creating code examples that should be well-documented
Core Principles
- Clarity: Documentation should be immediately understandable
- Completeness: Document all public APIs, parameters, returns, exceptions
- Consistency: Follow language-specific Google Style conventions
- Conciseness: Be thorough but avoid redundancy
- Examples: Include usage examples for complex functionality
Workflow
1. Detect Language
Identify the programming language:
- Python: Look for
.pyfiles,def,classkeywords, type hints - Go: Look for
.gofiles,func,type,packagekeywords - TypeScript: Look for
.ts/.tsxfiles,interface,type,export,importkeywords - Terraform: Look for
.tffiles,resource,variable,modulekeywords
2. Apply Appropriate Standard
Read the corresponding reference file:
- Python: Read
references/python_google_style.mdfor complete docstring standards - Go: Read
references/go_google_style.mdfor complete comment standards - TypeScript: Read
references/typescript_google_style.mdfor complete JSDoc standards - Terraform: Read
references/terraform_style.mdfor complete description standards
3. Document Code Elements
Apply documentation to all appropriate code elements:
Python:
- Module-level docstrings
- Class docstrings
- Method/function docstrings
- Important variables/constants
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 20d ago Changed · +36 lines 8c05aba56476
- 1mo ago First seen · 362 lines · 88 tokens per session scan A 60bb2848f6ec
document-code is a skill published in the GitHub repository jjmartres/ai-coding-agents (49 stars, last pushed 8d ago), licensed MIT. It adds 88 tokens to every session and 2,530 once invoked, about $0.0004 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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