{"categories":[{"label":"Quality Assurance","url":"https://skillfed.io/packages/category/software-development-quality-assurance/4"}],"enrichment":{"capability":"ATDD is a CLI toolkit that structures AI agent work into evidence-gated phases\u2014planning, testing, implementation, validation, refactor, and merge\u2014using pytest, YAML configuration, and JSON schema validation to enforce deterministic workflows.","skillfed_tags":["ai-agent-orchestration","test-driven-development","workflow-automation"],"use_cases":["Decompose ambiguous feature requests into executable work units with mandatory planning gates before implementation begins.","Run multiple AI agents on the same codebase without merge conflicts by isolating each issue in a worktree and enforcing sequential phase advancement.","Enforce red-green-refactor discipline by gating code advancement on passing tests, smoke evidence, and validator verdicts before merge.","Recover from interrupted agent sessions using JSONL event logs and resumable train runs.","Sync validation rules across different LLM providers (Claude, Codex, Gemini, GLM) via managed blocks that preserve user content.","Catch regressions before review by binding validator rules to issue IDs and enforcing per-rule dispositions."],"what_it_does":"ATDD is a command-line platform that turns vague work intent into a structured, evidence-gated train of execution phases. It uses pytest, YAML manifests, and JSON schema validation to enforce a deterministic lifecycle\u2014INIT \u2192 PLANNED \u2192 RED \u2192 GREEN \u2192 SMOKE \u2192 REFACTOR \u2192 COMPLETE \u2192 MERGED\u2014keeping planning, testing, and code synchronized. The toolkit is designed for AI agents to operate safely within clear boundaries: agents decompose work via gated planning sessions (Intent \u2192 Attach \u2192 Compose \u2192 Ratify \u2192 Author), then execute through supervised phases with mandatory evidence gates and validator dispositions.\n\nThe package depends on pyyaml for configuration, pytest and pytest-xdist for test execution and parallelization, jsonschema for validation, pytest-html for reporting, pytest-github-actions-annotate-failures for CI integration, and radon for code metrics. It is a CLI-first tool that integrates with GitHub Issues, Project v2 fields, and git worktrees to manage per-issue runtime isolation and prevent merge chaos. The train metaphor\u2014route, stations, cargo, tickets, signals, conductor\u2014maps to planned paths, lifecycle phases, features, WMBTs and acceptance claims, validators and CI, and operator supervision.","worth_installing":"Yes, if you are building AI-agent-driven development workflows and need deterministic phase enforcement, evidence gates, and supervisor control. The low install friction, active maintenance, and permissive license make it safe to adopt. No, if you need a library for embedding in existing Python applications\u2014ATDD is a CLI-first platform designed for GitHub-integrated local workflows. Verify that the decomposition target (resumable runs, optional Temporal backends) and multi-agent testing are production-ready for your use case."},"id":"atdd","links":{"html":"https://skillfed.io/packages/atdd","md":"https://skillfed.io/packages/atdd.md","pypi":"https://pypi.org/project/atdd/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-09","license_spdx":null,"license_treatment":"permissive","name":"atdd","python_support":"supports_current","summary":"ATDD Platform - Acceptance Test Driven Development toolkit"},"popularity":{"monthly_downloads":83931,"position":14040,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"4.40.0"}