simplify

name	simplify
description	Use after making code changes, before committing, or when the user asks to "simplify", "clean up", or "review" recent edits — runs three parallel review agents (reuse, quality, efficiency) over the diff and fixes the findings.

Simplify: Code Review and Cleanup

Review all changed files for reuse, quality, and efficiency. Fix any issues found.

Phase 1: Identify Changes

Run git diff (or git diff HEAD if there are staged changes) to see what changed. If there are no git changes, review the most recently modified files that the user mentioned or that you edited earlier in this conversation.

Phase 2: Launch Three Review Agents in Parallel

Use the subagent tool to launch all three reviewers concurrently in a single call. Each task gets the full diff plus its review angle. Use the reviewer builtin with explicit "report findings only, do not edit files" instructions so the main agent stays the single writer.

Always write findings to an OS temp directory, not the repo root.

tmp_dir=${TMPDIR:-/tmp}
findings_dir=$(mktemp -d "${tmp_dir%/}/simplify-findings-XXXXXX")
echo "$findings_dir"

// Replace <findings_dir> with path created by mktemp.
subagent({
  tasks: [
    {
      agent: "reviewer",
      task: "Code reuse review. Report findings only, do not edit files.\n\nDiff:\n<paste full diff>\n\n<paste Agent 1 instructions below>",
      output: "<findings_dir>/reuse-findings.md"
    },
    {
      agent: "reviewer",
      task: "Code quality review. Report findings only, do not edit files.\n\nDiff:\n<paste full diff>\n\n<paste Agent 2 instructions below>",
      output: "<findings_dir>/quality-findings.md"
    },
    {
      agent: "reviewer",
      task: "Efficiency review. Report findings only, do not edit files.\n\nDiff:\n<paste full diff>\n\n<paste Agent 3 instructions below>",
      output: "<findings_dir>/efficiency-findings.md"
    }
  ],
  concurrency: 3
})

If the diff is large, write it to a temp file in findings_dir and reference it by path in each task instead of inlining.

Agent 1: Code Reuse Review

For each change:

1. Search for existing utilities and helpers that could replace newly written code. Look for similar patterns elsewhere in the codebase — common locations are utility directories, shared modules, and files adjacent to the changed ones.
2. Flag any new function that duplicates existing functionality. Suggest the existing function to use instead.
3. Flag any inline logic that could use an existing utility — hand-rolled string manipulation, manual path handling, custom environment checks, ad-hoc type guards, and similar patterns are common candidates.

Agent 2: Code Quality Review

Review the same changes for hacky patterns:

1. Redundant state: state that duplicates existing state, cached values that could be derived, observers/effects that could be direct calls
2. Parameter sprawl: adding new parameters to a function instead of generalizing or restructuring existing ones
3. Copy-paste with slight variation: near-duplicate code blocks that should be unified with a shared abstraction
4. Leaky abstractions: exposing internal details that should be encapsulated, or breaking existing abstraction boundaries
5. Stringly-typed code: using raw strings where constants, enums (string unions), or branded types already exist in the codebase
6. Unnecessary JSX nesting: wrapper Boxes/elements that add no layout value — check if inner component props (flexShrink, alignItems, etc.) already provide the needed behavior
7. Nested conditionals: ternary chains (a ? x : b ? y : ...), nested if/else, or nested switch 3+ levels deep — flatten with early returns, guard clauses, a lookup table, or an if/else-if cascade
8. Unnecessary comments: comments explaining WHAT the code does (well-named identifiers already do that), narrating the change, or referencing the task/caller — delete; keep only non-obvious WHY (hidden constraints, subtle invariants, workarounds)

Agent 3: Efficiency Review

Review the same changes for efficiency:

1. Unnecessary work: redundant computations, repeated file reads, duplicate network/API calls, N+1 patterns
2. Missed concurrency: independent operations run sequentially when they could run in parallel
3. Hot-path bloat: new blocking work added to startup or per-request/per-render hot paths
4. Recurring no-op updates: state/store updates inside polling loops, intervals, or event handlers that fire unconditionally — add a change-detection guard so downstream consumers aren't notified when nothing changed. Also: if a wrapper function takes an updater/reducer callback, verify it honors same-reference returns (or whatever the "no change" signal is) — otherwise callers' early-return no-ops are silently defeated
5. Unnecessary existence checks: pre-checking file/resource existence before operating (TOCTOU anti-pattern) — operate directly and handle the error
6. Memory: unbounded data structures, missing cleanup, event listener leaks
7. Overly broad operations: reading entire files when only a portion is needed, loading all items when filtering for one

Phase 3: Fix Issues

Wait for all three agents to complete. Aggregate their findings and fix each issue directly. If a finding is a false positive or not worth addressing, note it and move on — do not argue with the finding, just skip it.

When done, briefly summarize what was fixed (or confirm the code was already clean), then delete the temp directory:

rm -rf "$findings_dir"

Related Skills

• requesting-code-review - Use for broader review beyond reuse, quality, and efficiency cleanup.
• verification-before-completion - Terminal gate for this workflow. Before claiming cleanup is complete, findings are handled, or the diff is clean, run fresh verification and report evidence.