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/darellchua2/opencode-config-template/docstring-generator-skillnpx skills add darellchua2/opencode-config-template --skill docstring-generator-skillgit clone --depth 1 https://github.com/darellchua2/opencode-config-templateWrote 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/darellchua2/opencode-config-template/docstring-generator-skill)<a href="https://agentmods.dev/skills/darellchua2/opencode-config-template/docstring-generator-skill"><img src="https://agentmods.dev/badge/skills/darellchua2/opencode-config-template/docstring-generator-skill.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 5.1 | $0.00040 | $0.04506 |
| Opus 5 | $0.00020 | $0.02253 |
| Sonnet 5 | $0.00008 | $0.00901 |
| Haiku 4.5 | $0.00004 | $0.00451 |
Grade A, and why
docstring-generator-skill 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.
How it starts
The opening of the file, as written. The whole thing — 740 lines — stays where its author put it; the contents beside it link to each section on GitHub.
What I do
I generate language-specific docstrings and documentation following industry standards:
- Detect Language: Analyze file extension and project structure to determine language
- Detect Docstring Style: Identify existing docstring conventions in codebase
- Generate Docstrings: Create appropriate docstrings following language conventions
- Support Multiple Formats:
- Python: PEP 257 (Google, NumPy, Sphinx/reST styles)
- Java: Javadoc format with @param, @return, @throws
- TypeScript: JSDoc/TSDoc format with @param, @returns, @throws
- C#: XML documentation comments with , , ,
- Handle Various Types: Functions, methods, classes, interfaces, properties, exceptions
- Enforce Documentation: Ensure docstrings are added during PR workflow
When to use me
Use this workflow when:
- Implementing new functions, classes, or methods in Python, Java, TypeScript, or C#
- Refactoring code and updating documentation
- Creating new APIs or public interfaces
- Following documentation best practices and industry standards
- Need to ensure all public code has proper docstrings
- Preparing code for code review and maintainability
Integration: This skill integrates with pr-creation-workflow and linting-workflow to enforce docstring presence as part of quality checks.
Prerequisites
- Source code files (.py, .java, .ts, .tsx, .cs, .csx)
- File permissions to read and write files
- Knowledge of preferred docstring style (optional, can auto-detect)
- For workflow integration: Git repository initialized
Supported Languages and Standards
Python
Standard: PEP 257 compliant Supported Styles:
- Google Style (recommended for most projects)
- NumPy Style (for scientific computing)
- Sphinx/reST Style (for documentation generation)
Features:
- Type hints support (Python 3.5+)
- Exception documentation with Raises section
- Parameter documentation with Args section
- Return value documentation with Returns section
- Example code blocks in docstrings
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 · 740 lines · 40 tokens per session scan A 9139478ff608
docstring-generator-skill is a skill published in the GitHub repository darellchua2/opencode-config-template (6 stars, last pushed 5d ago), licensed Apache-2.0. It adds 40 tokens to every session and 4,506 once invoked, about $0.0002 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 2026-09-03.
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