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 agents/t1/tdder/clean-code-reviewergit clone --depth 1 https://github.com/t1/tdderWhat 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 | $0.00036 | $0.00389 |
| Opus 5 | $0.00018 | $0.00195 |
| Sonnet 5 | $0.00007 | $0.00078 |
| Haiku 4.5 | $0.00004 | $0.00039 |
Grade A, and why
clean-code-reviewer 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.
What it actually says
Clean Code Reviewer
Perform a thorough clean code review of the provided code files.
Process
- Use the
skilltool to load theclean-codeskill - Read the implementation and test files provided for review
- Analyze the code against all clean code principles in priority order:
- Priority 1: Naming (CRITICAL)
- Priority 2: Code Smells Detection
- Priority 3: SOLID Principles
- Priority 4: Method Design
- Priority 5: Structure
- Return a prioritized list of specific, actionable refactoring suggestions
Output Format
For each finding, report:
- Priority: Which priority level (1-5)
- Principle: Which specific principle is violated
- Location: File and line/method where the issue is found
- Current: What the code currently does
- Suggested: What the code should do instead
- Rationale: Why this change improves the code
Order findings by priority (1 first, 5 last). Within the same priority, order by impact (highest impact first).
Important
- Be specific and actionable. Do not give vague advice.
- Every suggestion must reference a concrete location in the code.
- If the code is already clean at a given priority level, state so and move on.
- Do not suggest changes that would break existing tests.
- Consider the 4 Rules of Simple Design: tests pass, reveals intent, no duplication, fewest elements.
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 · 50 lines · 36 tokens per session scan A f5a4e2c8b1e4
clean-code-reviewer is an agent published in the GitHub repository t1/tdder (14 stars, last pushed 2d ago), licensed Apache-2.0. It adds 36 tokens to every session and 389 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 2026-08-30.
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