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 skills/jeffallan/claude-skills/code-documenternpx skills add Jeffallan/claude-skills --skill code-documentergit clone --depth 1 https://github.com/Jeffallan/claude-skillsWrote 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/jeffallan/claude-skills/code-documenter)<a href="https://agentmods.dev/skills/jeffallan/claude-skills/code-documenter"><img src="https://agentmods.dev/badge/skills/jeffallan/claude-skills/code-documenter.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 | $0.00080 | $0.01306 |
| Opus 5 | $0.00040 | $0.00653 |
| Sonnet 5 | $0.00016 | $0.00261 |
| Haiku 4.5 | $0.00008 | $0.00131 |
Grade A, and why
code-documenter 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- code-documenter — 94% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Documenter
Documentation specialist for inline documentation, API specs, documentation sites, and developer guides.
When to Use This Skill
Applies to any task involving code documentation, API specs, or developer-facing guides. See the reference table below for specific sub-topics.
Core Workflow
- Discover - Ask for format preference and exclusions
- Detect - Identify language and framework
- Analyze - Find undocumented code
- Document - Apply consistent format
- Validate - Test all code examples compile/run:
- Python:
python -m doctest file.pyfor doctest blocks;pytest --doctest-modulesfor module-wide checks - TypeScript/JavaScript:
tsc --noEmitto confirm typed examples compile - OpenAPI: validate spec with
npx @redocly/cli lint openapi.yaml - If validation fails: fix examples and re-validate before proceeding to the Report step
- Python:
- Report - Generate coverage summary
Quick-Reference Examples
Google-style Docstring (Python)
def fetch_user(user_id: int, active_only: bool = True) -> dict:
"""Fetch a single user record by ID.
Args:
user_id: Unique identifier for the user.
active_only: When True, raise an error for inactive users.
Returns:
A dict containing user fields (id, name, email, created_at).
Raises:
ValueError: If user_id is not a positive integer.
UserNotFoundError: If no matching user exists.
"""
NumPy-style Docstring (Python)
def compute_similarity(vec_a: np.ndarray, vec_b: np.ndarray) -> float:
"""Compute cosine similarity between two vectors.
Parameters
----------
vec_a : np.ndarray
First input vector, shape (n,).
vec_b : np.ndarray
Second input vector, shape (n,).
Returns
-------
float
Cosine similarity in the range [-1, 1].
Raises
------
ValueError
If vectors have different lengths.
"""
JSDoc (TypeScript)
/**
* Fetches a paginated list of products from the catalog.
*
* @param {string} categoryId - The category to filter by.
* @param {number} [page=1] - Page number (1-indexed).
* @param {number} [limit=20] - Maximum items per page.
* @returns {Promise<ProductPage>} Resolves to a page of product records.
* @throws {NotFoundError} If the category does not exist.
*
* @example
* const page = await fetchProducts('electronics', 2, 10);
* console.log(page.items);
*/
async function fetchProducts(
categoryId: string,
page = 1,
limit = 20
): Promise<ProductPage> { ... }
What ships with it
8 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.
- references/api-docs-fastapi-django.md 4.1 KB
- references/api-docs-nestjs-express.md 4.8 KB
- references/coverage-reports.md 3.0 KB
- references/documentation-systems.md 5.9 KB
- references/interactive-api-docs.md 10.0 KB
- references/python-docstrings.md 2.9 KB
- references/typescript-jsdoc.md 3.0 KB
- references/user-guides-tutorials.md 11 KB
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 · 150 lines · 80 tokens per session scan A 9db40547fcaf
code-documenter is a skill published in the GitHub repository Jeffallan/claude-skills (11,307 stars, last pushed 27d ago), licensed MIT. It adds 80 tokens to every session and 1,306 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
codebase-recon
Trace a repo into cited flows. Not for a bounded question; that is research. Triggers: "codebase recon", "trace this codebase", "repository audit", "refresh the prior recon".
converter
Convert AgentOps skill formats. Triggers: "converter", "convert agentops skill formats.", "converter skill".
reverse-engineer
Inventory an authorized repo, binary, or product. Not for tracing your own repo; that is codebase-recon. Triggers: "reverse-engineer X", "tear down Y", "what should we steal from Z", "evaluate competitor/upstream", "should we fork/adopt/build-native".
test
Generate tests and coverage plans. Triggers: "test", "generate tests and coverage plans.", "test skill".
skill-builder
Create a metadata-complete AgentOps skill source package, regenerate its derived projections, and check or repair structural hygiene in skill packages. Triggers: "create a skill", "scaffold skill", "absorb external skill", "new skill", "heal skill", "repair skill hygiene", "audit skill structure", "check skill…
anti-ceremony
Guard outcome work against process overhead. Triggers: RPI pre-Plan guard; explicit "full anti-ceremony audit" requests.