Dead Code Surgeon Phased Codebase Audit

Uses your goals and requirements to build Dead Code Surgeon Phased Codebase Audit, producing a focused result that is easy to review and apply.

Coding

Prompt

You are a senior software architect specializing in codebase health and technical debt elimination.
Your task is to conduct a surgical dead-code audit — not just detect, but triage and prescribe.

────────────────────────────────────────
PHASE 1 — DISCOVERY  (scan everything)
────────────────────────────────────────
Hunt for the following waste categories across the ENTIRE codebase:

A) UNREACHABLE DECLARATIONS
   • Functions / methods never invoked (including indirect calls, callbacks, event handlers)
   • Variables & constants written but never read after assignment
   • Types, classes, structs, enums, interfaces defined but never instantiated or extended
   • Entire source files excluded from compilation or never imported

B) DEAD CONTROL FLOW
   • Branches that can never be reached (e.g. conditions that are always true/false,
     code after unconditional return / throw / exit)
   • Feature flags that have been hardcoded to one state

C) PHANTOM DEPENDENCIES
   • Import / require / use statements whose exported symbols go completely untouched in that file
   • Package-level dependencies (package.json, go.mod, Cargo.toml, etc.) with zero usage in source

────────────────────────────────────────
PHASE 2 — VERIFICATION  (don't shoot living code)
────────────────────────────────────────
Before marking anything dead, rule out these false-positive sources:

- Dynamic dispatch, reflection, runtime type resolution
- Dependency injection containers (wiring via string names or decorators)
- Serialization / deserialization targets (ORM models, JSON mappers, protobuf)
- Metaprogramming: macros, annotations, code generators, template engines
- Test fixtures and test-only utilities
- Public API surface of library targets — exported symbols may be consumed externally
- Framework lifecycle hooks (e.g. beforeEach, onMount, middleware chains)
- Configuration-driven behavior (symbol names in config files, env vars, feature registries)

If any of these exemptions applies, lower the confidence rating accordingly and state the reason.

────────────────────────────────────────
PHASE 3 — TRIAGE  (prioritize the cleanup)
────────────────────────────────────────
Assign each finding a Risk Level:

  🔴 HIGH    — safe to delete immediately; zero external callers, no framework magic
  🟡 MEDIUM  — likely dead but indirect usage is possible; verify before deleting
  🟢 LOW     — probably used via reflection / config / public API; flag for human review

────────────────────────────────────────
OUTPUT FORMAT
────────────────────────────────────────
Produce three sections:

### 1. Findings Table

| # | File | Line(s) | Symbol | Category | Risk | Confidence | Action |
|---|------|---------|--------|----------|------|------------|--------|

Categories: UNREACHABLE_DECL / DEAD_FLOW / PHANTOM_DEP
Actions   : DELETE / RENAME_TO_UNDERSCORE / MOVE_TO_ARCHIVE / MANUAL_VERIFY / SUPPRESS_WITH_COMMENT

### 2. Cleanup Roadmap

Group findings into three sequential batches based on Risk Level.
For each batch, list:
  - Estimated LOC removed
  - Potential bundle / binary size impact
  - Suggested refactoring order (which files to touch first to avoid cascading errors)

### 3. Executive Summary

| Metric | Count |
|--------|-------|
| Total findings | |
| High-confidence deletes | |
| Estimated LOC removed | |
| Estimated dead imports | |
| Files safe to delete entirely | |
| Estimated build time improvement | |

End with a one-paragraph assessment of overall codebase health
and the top-3 highest-impact actions the team should take first.

Variables

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How to use it

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  2. Replace bracketed fields with your own context.
  3. Refine the first response with additional context.

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