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/jenreh/appkit/code-cleanupnpx skills add jenreh/appkit --skill code-cleanupgit clone --depth 1 https://github.com/jenreh/appkitWhat 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 | $0.00046 | $0.00486 |
| Opus 5 | $0.00023 | $0.00243 |
| Sonnet 5 | $0.00009 | $0.00097 |
| Haiku 4.5 | $0.00005 | $0.00049 |
Grade A, and why
code-cleanup 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
Code Cleanup
Target files
If $ARGUMENTS is provided, use those files. Otherwise, run:
git diff --name-only HEAD && git ls-files --others --exclude-standard
Filter the output to .py files only — those are the files to clean up.
If no modified Python files are found, report that and stop.
Rules
- Minimal diff — change only what clearly improves the file; do not restructure things that already work.
- No new features — preserve all existing behavior exactly.
- Per-file scope — do not modify files outside the target list unless an import must be fixed.
What to apply (per file)
- Remove dead code, unused imports, redundant comments, and unnecessary variables.
- Simplify overly complex conditionals; prefer early returns over deep nesting.
- Break functions > 20 lines into focused, well-named helpers — but only when the split is obvious.
- Replace verbose loops with list/dict/set comprehensions or generator expressions where readable.
- Ensure every function and method has a type annotation.
- No
printstatements — uselogging(default level:logger.debug). - No f-strings in logger calls:
log.info("x: %s", x)notlog.info(f"x: {x}"). - If a file exceeds 1000 lines after refactoring, split it and update imports accordingly.
Process
- Determine the target file list as described above and show it to the user.
- For each file: read it, identify improvements, apply as a single focused edit pass.
- After all edits: run
task format && task lint && task typecheckand fix any issues. - Summarize what changed per file (one line per change group).
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 · 44 lines · 46 tokens per session scan A 830e4bb71acd
code-cleanup is a skill published in the GitHub repository jenreh/appkit (4 stars, last pushed 6d ago), licensed MIT. It adds 46 tokens to every session and 486 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 2026-08-31.
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