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 rules/itamarzand88/awesome-agent-conventions/clean-codegit clone --depth 1 https://github.com/ItamarZand88/awesome-agent-conventionsWhat 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 | $0.00408 | $0.00408 |
| Opus 5 | $0.00204 | $0.00204 |
| Sonnet 5 | $0.00082 | $0.00082 |
| Haiku 4.5 | $0.00041 | $0.00041 |
Grade A, and why
clean-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 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
92% identical to clean-code — 1 line 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.
What it actually says
description: Guidelines for writing clean, maintainable, and human-readable code. Apply these rules when writing or reviewing code to ensure consistency and quality. globs: ["**/*"] alwaysApply: false
Clean Code Guidelines
Constants Over Magic Numbers
- Replace hard-coded values with named constants
- Use descriptive constant names that explain the value's purpose
- Keep constants at the top of the file or in a dedicated constants file
Meaningful Names
- Variables, functions, and classes should reveal their purpose
- Names should explain why something exists and how it's used
- Avoid abbreviations unless they're universally understood
Smart Comments
- Don't comment on what the code does - make the code self-documenting
- Use comments to explain why something is done a certain way
- Document APIs, complex algorithms, and non-obvious side effects
Single Responsibility
- Each function should do exactly one thing
- Functions should be small and focused
- If a function needs a comment to explain what it does, it should be split
DRY (Don't Repeat Yourself)
- Extract repeated code into reusable functions
- Share common logic through proper abstraction
- Maintain single sources of truth
Clean Structure
- Keep related code together
- Organize code in a logical hierarchy
- Use consistent file and folder naming conventions
Encapsulation
- Hide implementation details
- Expose clear interfaces
- Move nested conditionals into well-named functions
Code Quality Maintenance
- Refactor continuously
- Fix technical debt early
- Leave code cleaner than you found it
Testing
- Write tests before fixing bugs
- Keep tests readable and maintainable
- Test edge cases and error conditions
Version Control
- Write clear commit messages
- Make small, focused commits
- Use meaningful branch names
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 · 58 lines · 408 tokens per session scan A d0f2e2134856
clean-code is a cursor rule published in the GitHub repository ItamarZand88/awesome-agent-conventions (29 stars, last pushed 1mo ago), licensed MIT. It adds 408 tokens to every session, about $0.0020 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to clean-code, differing in 1 line, and is treated as a copy.
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