# AI Project Workflow ## Project Rules Before changing code, inspect the existing project structure and follow local patterns. Do not perform unrelated refactors, formatting churn, dependency upgrades, or broad cleanup unless explicitly requested. If scope needs to expand, stop and explain why before continuing. ## Spec Layer For non-trivial feature, behavior, architecture, data, automation, or user-facing changes, create or update a written change artifact before implementation. If a spec or change artifact already exists, use it as the source of truth. Do not create a separate competing plan unless explicitly requested. ## Agent Discipline - clarify ambiguous requirements before implementation - prefer test-first or TDD for features and bug fixes - debug from root cause, not symptoms - review diffs before calling work complete - verify behavior with tests, browser checks, logs, screenshots, or reproducible commands Do not claim completion without evidence. ## Verification Before completion, run the relevant checks and report the commands and results. Project commands: - Install dependencies: `` - Run tests: `` - Run lint/typecheck: `` - Build: `` - Run E2E/browser checks: `` ## External Action Safety Treat networked and external actions as approval-required unless the user explicitly authorizes them. Ask before: - pushing commits - opening or merging PRs - deploying - modifying production data - posting or sending messages - changing credentials - running paid jobs - operating real third-party accounts Do not send private code, customer data, secrets, production logs, database exports, or credentials to untrusted agents, MCP servers, browser automation, or external services. ## Completion Criteria A task is complete only when: - the requested behavior is implemented - relevant checks pass or failures are clearly explained - user-facing behavior is verified when applicable - no unrelated changes were introduced - the final response reports what changed and what was verified