implement-with-tdd

name	implement-with-tdd
description	TDD implementation with AI code-review loop for a single ticket.
role	implementer
allowed-tools	[]
required-mcps	[]
entrypoint-script	scripts/run.py
inputs	{"ticket":{"type":"object","required":true}}
outputs	{"files_changed":{"type":"array"},"test_result":{"type":"object"},"commit_sha":{"type":"string"},"review_report":{"type":"object"},"rounds_used":{"type":"integer"}}
invokes-skills	["ai-code-review"]
llm	{"max_iterations":30,"temperature":0.2,"max_tokens":16000}
policies	{"self_heal_max_rounds":3,"reviewer_max_rounds":2,"require_tests":true}

implement-with-tdd

Implement a single ticket using a TDD cycle and iterate with AI code review until converged or max-rounds reached.

Inputs

• ticket (object, required): one task from plan-tasks / create-jira-tickets.

Outputs

• files_changed (string[])
• test_result (object): {passed: boolean, output: string}
• commit_sha (string): commit created at end of the loop
• review_report (object): final ai-code-review output
• rounds_used (integer)

Policies

• require_tests: true means a green command is not enough: the runtime must also detect at least one executable test in the workspace before the ticket can be reported as implemented.
• reviewer_max_rounds: 2 means the first blocker/major review finding is fed back to the implementer for one repair attempt before the task falls back to human intervention.