// Systematic debugging: reproduce, isolate, form hypotheses, instrument, fix, and add regression tests. Use when troubleshooting errors, failing tests, or unexpected behavior.
| name | superpowers-debug |
| description | Systematic debugging: reproduce, isolate, form hypotheses, instrument, fix, and add regression tests. Use when troubleshooting errors, failing tests, or unexpected behavior. |
Enforces a disciplined workflow for coding, debugging, refactoring, and automation: brainstorm -> plan -> implement with verification (prefer TDD) -> review -> finish. Use for almost any non-trivial change.
Produces a structured brainstorm: goals, constraints, risks, options, recommendation, and acceptance criteria. Use before non-trivial implementation or design changes.
Finalizes work: runs verification, summarizes changes, notes follow-ups, and ensures repo hygiene. Use at the end of an implementation or debugging session.
Writes an implementation plan with small steps, exact files to touch, and verification commands. Use before making non-trivial changes.
Implements reliable automations in Python for REST APIs: httpx/requests patterns, retries, timeouts, pagination, typing, config, logging, and tests. Use when writing Python scripts/services that call external APIs.
Builds reliable automations that integrate with REST APIs: auth, pagination, retries, rate limits, idempotency, webhooks, data mapping, and safe error handling. Use when calling external APIs, syncing systems, or building ETL-style workflows.