cleanup

cleanup is a skill for Claude Code from suxrobGM/jobpilot. It costs 95 tokens per session (2,867 once invoked), scanned A, original, MIT.

A review-and-refactor process for cleaning up code in any language or framework. It examines structure, unused code, duplication, coupling, over-complexity, and architecture before applying changes.

In plain words
What is it for?
Use it on files, folders, modules, packages, or features when you need to assess organization, find maintainability problems, and carry out a phased refactor.
Why use it?
It turns a broad cleanup request into a project-aware plan while aiming to preserve behavior and follow the project’s own conventions.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: mentions CLAUDE.md; mentions subagents; mentions AGENTS.md.

Good fit Use it on files, folders, modules, packages, or features when you need to assess organization, find maintainability problems, and carry out a phased refactor.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/suxrobgm/jobpilot/cleanup
Install

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.

Any agent
npx skills add suxrobGM/jobpilot --skill cleanup
Clone the repo
git clone --depth 1 https://github.com/suxrobGM/jobpilot

Made for: Claude Code.

Wrote 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.

agentmods badge for cleanup

README.md
[![agentmods](https://agentmods.dev/badge/skills/suxrobgm/jobpilot/cleanup.svg)](https://agentmods.dev/skills/suxrobgm/jobpilot/cleanup)
Your own site
<a href="https://agentmods.dev/skills/suxrobgm/jobpilot/cleanup"><img src="https://agentmods.dev/badge/skills/suxrobgm/jobpilot/cleanup.svg" alt="Measured on agentmods" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,867 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 93
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00095 $0.02867
Opus 5 $0.00048 $0.01434
Sonnet 5 $0.00019 $0.00573
Haiku 4.5 $0.00010 $0.00287

Measured 8d ago against content hash da50e2ad0e1b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

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 8d 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.

.claude/skills/cleanup/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Cleanup

Systematic review-then-refactor of a target path (file, folder, module, package, or feature) in any language or framework. Every judgment is calibrated against the host project's own conventions and the ecosystem's idioms, not generic taste. Behavior-preserving by default; architecture and pattern changes are in scope when they pass the net-simplification test (below). The argument is the target path(s); if none given, ask.

Process

1. Calibrate

  • Detect the stack: languages, package manifests, build system, framework(s), and the project's own verification commands (typecheck/compile, lint, tests, formatter). Read them from project docs and manifests - never guess. These commands are the gate for every later phase.
  • Read the project's conventions FIRST - CLAUDE.md/AGENTS.md, rules files, lint/formatter config, editorconfig. Note the size ceiling, naming scheme, comment policy, and framework idioms (e.g. an auto-memoizing compiler makes manual memoization a finding, not a virtue; a DI container makes new in handlers a finding).
  • Inventory the target's files with line counts, largest first.
  • Assess the safety net: does the verification harness actually cover the target? If tests are thin, prefer low-risk phases, lean harder on adversarial verification, and consider adding characterization tests before risky structural work.

2. Map the boundary

  • Find every consumer outside the target (grep the target's path/package/symbol names). Record which symbols cross the boundary - the public surface that moves/renames must preserve. If the target is a published library, the surface includes consumers you cannot see: treat its exported API as frozen unless the user says otherwise.
  • Invisible callers: enumerate symbols invoked without an import - framework-registered routes/handlers/lifecycle hooks, DI/IoC registrations, reflection and dynamic dispatch (getattr, Method.invoke, message selectors), serialization/ORM field names, config- or convention-referenced classes, CLI entry points, FFI exports, template references, scheduled jobs, migrations. Grep alone cannot prove these dead.
  • Map the reverse direction (what the target reaches into) and flag misfiled code: anything inside the target consumed only by a different feature, judged by who calls it and whose data it touches.
  • Enumerate adjacent plumbing - out-of-tree files that wire the target in: routes/pages/handlers that mount it, DI wiring, build/config entries, data-access helpers and cache keys, localization files, docs/feature-map entries, CI steps. Plumbing is review scope, not just context: dead code hides there, and moves inside the target often require updating it.

Read the full file on GitHub · 94 lines

Changes

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.

  1. 8d ago First seen · 94 lines · 95 tokens per session scan A da50e2ad0e1b

Subscribe to this mod's changes

cleanup is a skill published in the GitHub repository suxrobGM/jobpilot (65 stars, last pushed today), licensed MIT. It adds 95 tokens to every session and 2,867 once invoked, about $0.0005 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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