Tdd Dev Cycle Agent Skill
测试驱动开发 (TDD) 主干工作循环，包含分析、测试编写、开发、验证及带熔断的修复机制。
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/cafe3310/public-agent-skills --skill tdd-dev-cycleThe instruction itself
1 sections, as written by the authorTDD (测试驱动开发) 主干工作循环
本 Skill 定义了标准的 TDD 开发与验证循环。
适用场景
如果项目章程没有定义具体的工作流，助手默认遵循以下 TDD 主干工作循环。
流程详情
- 智能调度
- 优先处理 backlog 中
priority: high的任务。 - 在选定了任务后，将其从
docs/backlog/移动到docs/requirements/并更新状态为开发中，然后开始分析。
- 规划与澄清 (TDD)
- a. 分析需求: 如果模糊则提问，并更新需求文档。
- b. 解决冲突: 如果需求和项目级别章程冲突，则提问澄清如何处理。一般来说要更新章程中的设计。
- c. 定义验收标准: 优先编写自动化测试用例。
- d. COMMIT 1:
git commit -m "完成需求 {文件名} 的分析与测试用例，即将开发"
- 开发
- 根据测试用例进行编码实现。
- 开发完成 -> COMMIT
- COMMIT 2:
git commit -m "完成需求 {文件名} 的开发，即将验证"
- 验证与带熔断的修复循环
- a. 运行自动化测试。
- b. 成功:
- COMMIT 5:
git commit -m "需求 {文件名} 的开发和验证已经全部完成！" - 报告完成并循环。
- c. 失败 (第 N 次):
- COMMIT 3:
git commit -m "验证需求 {文件名} 时遇到问题 {问题描述} (第 N 次尝试)，即将修复" - 熔断检查: 若 N > 3 次，则触发熔断，停止，并向用户求助。
- 修复: 分析日志，定位原因，编写修复代码。
- COMMIT 4:
git commit -m "验证需求 {文件名} ，成功解决了问题 {问题描述} (第 N 次尝试)" - 返回步骤 5a 重新验证。
循环直至所有 backlog 任务完成、用户打断、指令变更或达到熔断条件。
Other skills for the same job
different authors, same section of the catalogue
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Use when implementing any feature or bugfix, before writing implementation code
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
How to use it
Take cafe3310/tdd-dev-cycle from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.