Dead Code Sweep

Dead Code Sweep

Systematic identification and removal of dead code, redundant implementations, and orphaned artifacts in codebases — particularly those maintained by coding agents with limited context windows.

Why Agent-Maintained Codebases Accumulate Cruft

Coding agents operate within narrow context windows. When refactoring, they often:

• Re-implement functionality without finding and removing the original
• Leave compatibility shims for interfaces that no longer exist
• Abandon helper functions after inlining their logic
• Create new files without deleting the ones they replace
• Duplicate type definitions across module boundaries
• Leave imports for symbols they stopped using mid-refactor

This cruft compounds. Each orphaned artifact misleads the next agent (or human), who wastes context budget reading code that does nothing.

Workflow

Phase 1: Scope and Inventory

Determine the analysis boundary.

If the user provides a scope (directory, file pattern, module), constrain all analysis to that scope.

If no scope is provided, analyze the full codebase. Start by reading the project structure:

1. Identify the primary language(s) and framework(s)
2. Map entry points (main files, route definitions, exported modules, test runners)
3. Note the build system and dependency configuration
4. Check for monorepo structure — analyze each package as a unit

Produce a brief inventory:

Language(s): TypeScript, Python
Entry points: src/index.ts, src/cli.ts
Build: esbuild via package.json scripts
Packages: 1 (single package)
Estimated LOC: ~4,200

Phase 2: Detection

Launch parallel sub-agents to scan for different categories of dead code. Read references/cruft-patterns.md for the full catalog of detection patterns.

Organize detection into these parallel tracks:

For each track, the sub-agent should:

1. Read references/cruft-patterns.md for detection strategies specific to that track
2. Search the codebase using Grep and Glob
3. Verify each candidate by tracing references — a symbol is only dead if zero live code paths reach it
4. Record findings with file path, line range, and evidence

Verification is critical. Common false positives to watch for:

• Symbols used via dynamic dispatch, reflection, or string-based lookups
• Framework-magic exports (e.g., Next.js page components, pytest fixtures, Rails conventions)
• Public API surface intended for external consumers
• Conditional imports behind feature flags or environment checks
• Decorator-registered or plugin-registered handlers
• CLI entry points referenced in package.json bin fields
• CSS class names referenced in templates or JSX as dynamic strings

When uncertain, mark as "needs review" rather than "confirmed dead."

Phase 3: Report

Consolidate all findings into a structured report at .claude/dead-code-report.md.

Organize findings by confidence level, then by category:

# Dead Code Sweep Report

**Scope:** [full codebase | specific path]
**Date:** [date]
**Estimated removable lines:** [count]

## Confirmed Dead (high confidence)

### Orphaned Files
- `src/utils/old-parser.ts` — Not imported anywhere. Superseded by `src/parser/index.ts`.
- ...

### Unused Exports
- `formatDate()` in `src/helpers.ts:42-58` — Exported but zero imports across codebase.
- ...

[...other categories...]

## Needs Review (uncertain)

### Possibly Dynamic
- `handleLegacyEvent()` in `src/events.ts:91` — No static imports, but may be registered dynamically.
- ...

For each finding, include:

• File path and line range
• What it is (function, class, file, type, constant, dependency)
• Why it appears dead (no imports, no references, superseded by X)
• Confidence (confirmed / needs review)

Phase 4: Cleanup with Approval

Present the report summary to the user and ask for approval before removing anything.

Use AskUserQuestion to present findings by category:

Found 12 confirmed dead items and 3 needing review.

Confirmed dead by category:
- 3 orphaned files (~280 lines)
- 5 unused exports (~120 lines)
- 2 redundant implementations (~90 lines)
- 2 orphaned dependencies

Which categories should I clean up?

Options: Remove all confirmed / Select categories / Review each item / Skip cleanup

For each approved category:

1. Remove the dead code
2. Clean up any imports that referenced the removed code
3. Remove empty files left after cleanup
4. Remove orphaned dependencies from the manifest
5. Run the project's lint/typecheck/build commands to verify nothing broke

If any removal causes a build or type error, immediately revert that specific removal and move the item to "needs review."

After cleanup, update the report with what was removed and what was kept.

Detection Principles

Trace from entry points, not from suspects

Start from known entry points and trace what's reachable, rather than starting from a suspect symbol and trying to prove it's used. The reachability approach has fewer false negatives.

Respect the module boundary

A symbol exported from a package's public API may be consumed by external code not visible in this repository. When analyzing libraries or packages with external consumers, only flag internal (non-public-API) dead code as "confirmed." Flag public API dead code as "needs review."

Look for clusters, not just individuals

Agent-generated cruft tends to cluster. When one dead function is found, examine its neighbors — the agent likely abandoned the entire section during a refactor. A dead file often has sibling dead files created in the same commit.

Use git history as a signal

When available, check when suspect code was last meaningfully modified. Code untouched across several refactor commits is more likely dead. Use git log --follow to trace renames and detect superseded files.