Agentset is an open-source platform for building retrieval-augmented generation applications, which let AI systems find relevant information from document collections before generating responses. Developers use it for ingestion, vector search, evaluation, cited chat, hosting, and agentic applications through APIs and SDKs. Its catalogue rules and skills provide agent guidance for working with Agentset.
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.
git clone --depth 1 https://github.com/agentset-ai/agentsetWrote 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/rules/agentset-ai/agentset/clean-code)<a href="https://agentmods.dev/rules/agentset-ai/agentset/clean-code"><img src="https://agentmods.dev/badge/rules/agentset-ai/agentset/clean-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/rules/agentset-ai/agentset/clean-code"><img src="https://agentmods.dev/badge/rules/agentset-ai/agentset/clean-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 | $0.00322 | $0.00322 |
| Opus 5.5 | $0.00129 | $0.00129 |
| Sonnet 5.5 | $0.00064 | $0.00064 |
| Haiku 4.5 | $0.00032 | $0.00032 |
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 2mo 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
84% identical to clean-code — 23 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.
What it actually says
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
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.
- 2mo ago First seen · 56 lines · 322 tokens per session scan A cf40932014f6
clean-code is a cursor rule published in the GitHub repository agentset-ai/agentset (2,123 stars, last pushed 9d ago), licensed MIT. It adds 322 tokens to every session, about $0.0013 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 84% identical to clean-code, differing in 23 lines, and is treated as a copy.
clean-code compared with cursor rules from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| clean-codeagentset-ai/agentset | Cursor rule | 2.1k | 9d ago | MIT | A | 322 | Cursor |
| defensive-invariantsctxr-dev/llm-wiki-memory | Cursor rule | 129 | 1mo ago | MIT | A | 87 | Cursor |
| triage-review-findingsctxr-dev/llm-wiki-memory | Cursor rule | 129 | 1mo ago | MIT | A | 49 | Cursor |
| requirement-reviewxiaozhi86/qamaster | Cursor rule | 6 | 2mo ago | MIT | A | 28 | Cursor |
| code-review-standardscarmentacollective/carmenta | Cursor rule | 2 | 4mo ago | none | A | 4 | Cursor |
| ponytailDietrichGebert/ponytail | Cursor rule | 185k | 8d ago | MIT | A | 604 | Cursor |
| angular-20angular/angular | Cursor rule | 101k | yesterday | MIT | A | 0 | Cursor |