mcpbeat

Simplify Code

hezaohezao/simplify-code

Sequential 3-lens cleanup of recent code changes.

2k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
117
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/HezaoHezao/poirot --skill simplify-code

What it tells the agent to use

found in the instruction text
Bash runs shell commands — read the instruction before connecting
Grep reads your files
Task spawns other agents

The instruction itself

8 sections, as written by the author

Simplify Code — Sequential Review & Cleanup

Review your recent code changes with three focused lenses, aggregate findings,

and apply the fixes worth applying.

Core principle: Three narrow reviews beat one broad review. Each one deeply

searches the codebase for a single class of problem — reuse, quality,

efficiency — without diluting attention across all three.

> Poirot note: The original skill runs 3 reviewers in parallel via

> subagent delegation. Poirot has no subagents, so this version runs the 3

> lenses sequentially in the same context. The methodology is identical;

> only the concurrency is lost.

When to Use

Trigger this skill when the user says any of:

  • "simplify" / "simplify my changes" / "simplify these changes"
  • "review my code" / "review my recent changes" / "clean up my changes"

Optional modifiers the user may add — honor them:

  • Focus: "simplify focus on efficiency" → run only the efficiency lens.

Recognized focuses: reuse, quality, efficiency.

  • Dry run: "simplify but don't change anything" / "just report" → run the

three lenses, present findings, apply NOTHING. Ask before applying.

  • Scope: "simplify the last commit" / "simplify staged" / "simplify

src/foo.py" → narrow the diff source accordingly.

Do NOT auto-run this after every edit. Invoke it only when the user asks.

The Process

Phase 1 — Identify the changes

Capture the diff to review. Pick the source by what the user asked for:

# 1. Default: uncommitted working-tree changes (tracked files)
git diff

# 2. If that's empty, include staged changes
git diff HEAD

# 3. Scoped variants:
git diff --staged                 # "staged changes"
git diff HEAD~1                    # "the last commit"
git diff main...HEAD              # "this branch" / "my PR"
git diff -- src/foo.py            # specific file(s)

If git diff and git diff HEAD are both empty, fall back to files the user

explicitly named or recently edited in this session. If you can't find any

changed code, say so and stop.

Capture the full diff text. Note its size: if >2000 changed lines, warn the

user and offer to scope down before proceeding.

Phase 2 — Run three lenses (sequentially)

Each lens gets the complete diff (not fragments — cross-file issues hide in

the gaps) plus the repo path so it can search the wider codebase via bash

(grep) and read_file.

For each lens:

  • Search the existing codebase for evidence (don't reason from the diff alone).
  • Apply Chesterton's Fence: before flagging anything for removal, run

git blame on the line to understand why it exists. If you can't determine

the original purpose, mark it confidence: low.

  • Report findings as structured output:
  file:line → problem → suggested fix | confidence: high/medium/low | risk: SAFE/CAREFUL/RISKY
  • SAFE = proven not to affect behavior (unused imports, commented-out

code, pass-through wrappers). Auto-apply these.

  • CAREFUL = improves without changing semantics (rename local variable,

flatten nested ternary, extract helper). Apply with test verification.

  • RISKY = may change behavior or breaks public contracts. Flag for

human review — do NOT auto-apply.

  • Skip nits and style-only churn.

Run these three lenses (skip any the user's focus excludes):

Lens 1 — Code Reuse

> Review this diff for code that duplicates functionality already in the

> codebase. Search utility modules, shared helpers, and adjacent files (use

> bash grep) for existing functions, constants, or patterns the new code

> could call instead of reimplementing. Flag: new functions that duplicate

> existing ones; hand-rolled logic that an existing utility already does. For

> each, name the existing thing to use and where it lives.

Lens 2 — Code Quality

> Review this diff for quality problems. Look for: redundant state; parameter

> sprawl; copy-paste-with-variation; leaky abstractions; stringly-typed code

> (raw strings where a constant/enum exists); AI-generated slop patterns

> (extra comments restating obvious code, unnecessary defensive null-checks,

> as any casts). For each, give the concrete refactor.

Lens 3 — Efficiency

> Review this diff for efficiency problems. Look for: unnecessary work

> (redundant computation, repeated file reads, N+1 access); missed concurrency;

> hot-path bloat; TOCTOU anti-patterns; memory issues (unbounded growth,

> missing cleanup); overly broad reads; silent failures (empty catch blocks,

> except: pass). For each, give the concrete fix and why it's faster/safer.

Phase 3 — Aggregate and apply

  • Merge the findings into one list, deduping where lenses overlap.
  • Discard false positives — you have the most context; drop weak or wrong

suggestions silently.

  • Resolve conflicts. Default resolution order:

correctness > the user's stated focus > readability/reuse > micro-perf.

Don't apply a perf "fix" that hurts clarity unless the path is genuinely hot.

  • Apply in risk-tier order:
  • SAFE first (auto-apply): unused imports, commented-out code,

pass-through wrappers. Run tests after.

  • CAREFUL next (apply with verification, one file at a time): rename

locals, flatten ternaries, extract helpers, consolidate dupes. Run tests

after each file. Revert any that break.

  • RISKY last (flag for review — do NOT auto-apply): N+1 restructuring,

public API changes, concurrency fixes. Present each with risk description

and test coverage status.

If the user opted for a dry run, present all three tiers and apply nothing.

  • Verify you didn't break anything: run the project's targeted tests for

the touched files, and re-run any linter/type check the repo uses. If a fix

breaks a test, revert that one fix and report it.

  • Summarize what you changed: a short list of applied fixes grouped by

lens and risk tier, plus any findings you deliberately skipped and why.

Pitfalls

  • Give the WHOLE diff to each lens. Splitting the diff defeats the design —

cross-file duplication and N+1s only show up with the full picture.

  • Lenses search, they don't guess. A reuse finding with no pointer to the

existing utility is noise. Require file:line evidence; drop findings that

lack it.

  • Apply ≠ rewrite. This is cleanup of the user's recent changes, not a

license to refactor the whole module. Keep edits scoped to what the diff

touched plus the minimal surrounding change a fix requires.

  • Respect project conventions. If the repo has AGENTS.md / CLAUDE.md

or a linter config, fold those rules into the lens prompts so suggestions

match house style.

  • Large diffs blow context. If the diff is huge, scope it down before

reviewing — a 5000-line diff may truncate.

  • Over-trusting dead code tools. knip, ts-prune, depcheck flag

exports that ARE used dynamically. Always grep for the symbol name before

removing — a clean tool report is not proof.

  • Renaming without checking public contracts. Export names, API route

paths, DB column names, config keys are contracts. Tag public-contract

changes as RISKY; never auto-rename them.

  • Removing "unnecessary" error handling. An empty catch block might be

intentional. Flag it, don't remove it; let the human decide.

Use requesting-code-review for the pre-commit security/quality gate.

This skill is the standalone *after-the-fact* cleanup pass.

How to use it

Copy the folder

Take hezaohezao/simplify-code from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.