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Autonomous TDD agents automate test-driven development by coordinating requirement clarification, planning, deterministic implementation, and interactive delivery verification. You describe a feature task, and the agent creates a SPEC, plans atomic tasks, and executes them with strict gate checks.

Development state management for autonomous agents uses ephemeral state directories for active execution context and committed documentation folders for final deliverables. This ensures atomic commits and gated execution maintain trackable progress across multi-task projects.

Autonomous TDD applies to bug fixes and multi-task projects across codebases of varying sizes, from small APIs to large systems. It enforces strict frontmatter-driven specifications and evidence-based verification to handle complex feature work.

Requirement clarification in autonomous development selects from Quick, Structured, or Deep depths to create a precise specification file. This adaptive process ensures the autonomous agent has exact parameters before planning atomic, test-driven implementation tasks.

Autonomous TDD execution plans features into single, test-driven tasks with strict gate checks and atomic commits. While the agent drives the implementation autonomously, it enforces evidence-based verification through interactive walkthroughs to ensure stakeholder acceptance.

You should avoid autonomous feature implementation when your project lacks clear acceptance criteria for interactive delivery verification, or when strict frontmatter-driven specifications cannot be established for the required deterministic, test-driven task execution.