Codebase Litter Audit

Codebase Litter Audit

Codex Compatibility

When running this skill in Codex, translate Claude Code-only primitives before acting: AskUserQuestion -> chat/request_user_input, TodoWrite -> update_plan, Task/TaskCreate/TeamCreate/SendMessage -> spawn_agent/send_input/wait_agent when available and allowed, and EnterPlanMode/ExitPlanMode -> a concise chat plan plus explicit approval. Resolve Read/Write/Edit/Bash/WebSearch/WebFetch to Codex file/shell/web tools, and map ~/.claude/... paths to ~/.agents/... or ~/.codex/... unless the task explicitly targets Claude Code.

Cursor Compatibility

When running this skill in Cursor Agent, translate Claude Code-only primitives before acting: AskUserQuestion -> AskQuestion; TodoWrite -> Cursor TodoWrite or an equivalent checklist; Task/TaskCreate/TeamCreate/SendMessage/multi-agent flows -> Cursor Task (subagents), parallel Tasks, or run_in_background when allowed (TeamCreate/SendMessage may have no exact match); EnterPlanMode/ExitPlanMode -> Plan mode (SwitchMode / CreatePlan) plus explicit approval. Resolve Read/Write/Edit/StrReplace/Bash/web/search/MCP via Cursor Composer or Agent equivalents. MCP names written as mcp__server__tool typically map to call_mcp_tool with configured server identifiers. Map ~/.claude/... to ~/.cursor/skills/, .cursor/skills/, and .cursor/rules/ unless the task explicitly targets Claude Code.

Overview

Find incomplete or misleading work that is still reachable, visible, or confusing even when dead-code scanners report nothing. Treat the scanner as a lead generator, then verify each finding by reading neighboring code, tests, docs, and issue tracker context.

Workflow

1. Establish scope.

   • Run git status --short and note whether the worktree is dirty.
   • Identify the repo root and primary tracker (gh issue list when GitHub is configured).
   • Do not edit files unless the user explicitly asks for cleanup.

2. Collect candidate signals.

   • Prefer the bundled scanner:

python3 ~/.codex/skills/codebase-litter-audit/scripts/scan_litter.py . --markdown

• If the repo is huge, pass focused paths after the repo root: --include src --include e2e.
• Supplement with rg for domain words the scanner cannot infer, such as feature names, issue IDs, or product terminology.

3. Verify candidates manually.

   • Read the candidate line and nearby code.
   • Trace one call site, UI surface, test, or doc reference before calling it real.
   • Search for later migrations, docs, PRs, or issues that may supersede an old TODO.
   • Classify stale comments separately from active defects.

4. Report with evidence.

   • Lead with high-confidence, user-visible, or security-relevant litter.
   • Anchor every claim to a clickable file path and line.
   • Include severity as High, Medium, or Low.
   • State the smallest cleanup path: remove UI, implement behavior, unskip/replace test, update docs, or close as stale.
   • Mention likely duplicate/open issues if found.

What Counts

Use references/signal-catalog.md when deciding whether a candidate is worth reporting.

Strong signals:

• Visible commands, routes, buttons, menus, settings, or CLI options wired to stubs or no-op handlers.
• TODO, FIXME, not implemented, stub, temporary, or WIP attached to reachable product code.
• Tests skipped for real product behavior, especially persistence, auth, security, data loss, or critical flows.
• Comments or docs that contradict later code, migrations, or configuration.
• Placeholder assets or copy that can ship to users.
• Suppressions such as eslint-disable, ts-ignore, @ts-expect-error, or broad ignores with no issue link or expiry.

Weak signals:

• Example text in stories/tests.
• Placeholder attributes in normal forms.
• Historical migration comments already superseded by a later migration.
• Generated files, lockfiles, vendored code, or .git hook samples.

Output Template

## Codebase Litter Audit

### Findings

- **Medium: <short title>**
  Evidence: [file.ts](/abs/path/file.ts:12)
  Why it matters: <reachable/visible/confusing behavior>
  Smallest cleanup: <implement/remove/document/issue>

### Probably Benign

- <candidate that looked suspicious but was superseded or test-only>

### Suggested Issues

- <one issue per actionable cleanup, with labels if the tracker supports them>

Bundled Resources

• scripts/scan_litter.py: candidate scanner that emits Markdown or JSON.
• references/signal-catalog.md: classification guide for deciding what is real litter versus normal code.