--- name: razor description: Use when questioning whether code in a folder should exist, whether a solution is over-engineered, or where maintenance cost can be cut. argument-hint: --- target_path = $ARGUMENTS If no target path provided, ask for one. This skill requires a concrete scope — "the whole repo" produces shallow findings. ## Purpose Every line of code is a liability — read, understood, maintained, debugged, migrated. This skill makes maintenance cost visible and challenges code that doesn't earn its keep. This is not a correctness review or a style review. The question: **should this code exist at all, and if so, at this size?** ## Reconnaissance Before spawning reviewers, build the brief they all share: 1. Map the scope — file count, total LOC, directory structure, entry points 2. Identify the feature set — what user-facing capabilities does this code provide? List concretely. 3. Detect the stack — languages, frameworks, key dependencies 4. Find existing docs — any stated purpose or architecture rationale ## Teammates Spawn all three from `${CLAUDE_SKILL_DIR}/agents/` **in parallel**. All are **read-only** — analysis only, no edits. Each gets the full brief plus all file paths in the target. | Teammate | Agent file | Lens | |----------|-----------|------| | YAGNI Enforcer | `yagni.md` | What here solves a problem nobody actually has? | | Cost Auditor | `cost-auditor.md` | What's the maintenance burden vs. the value delivered? | | Alternatives Scout | `alternatives.md` | What existing libraries, services, or simpler architectures could replace this? | ## Synthesis ### Credibility Filter Discard findings that fail any of these: - **Evidence-based** — references specific files, line counts, complexity metrics, or usage patterns. Speculation is not a finding. - **Proportionate** — a 30-line utility being "unnecessary" isn't worth reporting; a 500-line abstraction wrapping a 10-line operation is. The model's instinct is to report everything it finds — resist this. Only surface findings where the cost/value mismatch is material. - **Alternative-bearing** — "delete this" is not actionable. "Replace this 400-line custom parser with `{library}`" is. - **Honest about migration cost** — removing/replacing code has a cost too. Acknowledge it. Discard findings where the reviewer misunderstood the feature's purpose. Discard findings about code that's necessary but could be slightly shorter — that's refactoring territory, not razor territory. ### Severity | Level | Meaning | |-------|---------| | **CUT** | Maintenance cost clearly exceeds value. Concrete alternative exists. | | **SHRINK** | Feature is justified but implementation is 3-10x larger than necessary. | | **QUESTION** | Unclear whether this earns its keep. Needs user context — state the specific question. | | **KEEP** | Reviewers challenged it and it survived. Note what was challenged and why it stood — this builds trust that the review is fair, not just aggressive. | ### Report Structure 1. **Scope summary** — what was reviewed (files, LOC, features) 2. **Headline** — one sentence: lean, reasonable, or bloated? 3. **CUT list** — what to remove/replace, with alternatives and estimated LOC reduction 4. **SHRINK list** — what to simplify, with the simpler approach sketched 5. **QUESTION list** — what needs user context (state the specific question) 6. **KEEP list** — what survived the challenge 7. **If starting fresh** — knowing what we know now, what's the minimal architecture delivering the same capabilities? **Stop after the report. Do not implement changes unless asked.** ### Failure Modes - **Drive-by severity inflation.** The model tends to rate everything CUT or SHRINK to look thorough. A report with zero KEEP items signals the review failed, not that the code is bad. Calibrate: most well-maintained codebases have more KEEP than CUT. - **Ignoring migration cost.** "Replace with library X" sounds clean until you account for the API surface, test rewrite, and behavior differences. Every recommendation must acknowledge what the switch costs. - **Misreading domain code as over-engineering.** Domain-specific abstractions (workflow engines, rule systems, protocol handlers) look like speculative architecture to a generalist reviewer. When code serves a domain you don't fully understand, classify as QUESTION, not CUT.