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Use after making code changes, before committing, or before claiming work is done. Runs type-check → lint → test → build and fixes failures immediately.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | verify |
| description | Use after making code changes, before committing, or before claiming work is done. Runs type-check → lint → test → build and fixes failures immediately. |
You verify your work before claiming it's done. Never say "the changes are complete" without evidence.
Run these in order. Stop on first failure and fix before continuing.
# TypeScript
bun tsc --noEmit
# or npx tsc --noEmit
# Python
mypy . || pyright .
# Check package.json scripts for lint command
# Common: bun run lint, npm run lint, cargo clippy, go vet
# Check package.json scripts for test command
# Common: bun test, npm test, cargo test, go test ./..., pytest
# Common: bun run build, npm run build, cargo build
package.json, Makefile, Cargo.toml, etc. Don't guess.foo.ts, run foo.test.ts before the full suite.If the project has no tests, no type-checker, and no linter:
After verification, summarize briefly:
Type check: pass
Lint: pass
Tests: 42/42 passing
Or if something failed:
Tests: 41/42 passing — `test_auth_flow` failing (assertion error on line 58)
Fixing...
System design and architecture decisions. Use when planning new features, evaluating trade-offs, or designing how components should connect. Proposes 2-3 approaches and recommends one.
Smart commit workflow. Reviews staged changes, writes conventional commit messages, and catches issues before committing. Use when ready to commit work.
Quality review of completed work. Use after making changes and before claiming completion. Reviews code for correctness, edge cases, security, and maintainability.
Systematic debugging workflow. Use when diagnosing bugs, test failures, or unexpected behavior. Follows a rigorous reproduce → isolate → hypothesize → fix → verify cycle.
Systematic multi-agent research. Use when you need to deeply investigate a topic, codebase, or question by spawning parallel research agents and synthesizing their findings.
Deep code explanation. Use when you need to understand or explain how a system, module, or function works. Traces data flow, maps dependencies, and explains design decisions.