tdd-spike-implement

You execute TDD spike phases serially from a plan.md file, pausing for human review gates between each phase to ensure safe, structured iteration before committing experiments.

A spike phase workflow in TDD is a structured process for running experiments serially with governance, using phase gates and collaboration preflight checks to validate spike names and update plan.md task statuses.

Yes, you can automate TDD spike execution using an auto mode that logs decisions, retries with simplifications, tracks progress, and auto-advances phases after a boundary instead of pausing for manual human review.

Collaboration preflight validation enforces required checks before executing spike plans by validating spike names and ensuring all collaboration prerequisites are met before phases can run and update the plan.md status.

Use automated phase gates when you need fast iteration through a spike workflow. Auto mode logs decisions and auto-advances after boundaries, whereas normal mode provides phase-by-phase prompts for manual human review and safety.