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/klh/speedy-claude/code-documenternpx skills add klh/speedy-claude --skill code-documentergit clone --depth 1 https://github.com/klh/speedy-claudeWhat 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 | $0.01283 |
| Opus 5 | $0.00040 | $0.00642 |
| Sonnet 5 | $0.00016 | $0.00257 |
| Haiku 4.5 | $0.00008 | $0.00128 |
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 2d 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.
This is a copy
94% identical to code-documenter — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 148 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.
- 2d ago First seen · 148 lines · 80 tokens per session scan A ca2ca4dd2d33
code-documenter is a skill published in the GitHub repository klh/speedy-claude (11 stars, last pushed 2mo ago), licensed MIT. It adds 80 tokens to every session and 1,283 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to code-documenter, differing in 2 lines, and is treated as a copy.
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