| 測試案例產生器 — 把 PRD 的驗收標準(Acceptance Criteria)與規則,轉成 QA 可直接執行的 測試案例:正常路徑、邊界值、異常路徑、併發/冪等、權限與安全。 當使用者說「幫我寫測試案例」、「這份 PRD 的 test case」、「QA 測試計畫」、「幫我補測試」、 「這功能怎麼測」、「寫測試」、「test cases」、「test plan」、「QA checklist」時, 一定要使用這個 skill。即使使用者只是丟一份 PRD、一段 AC、一個功能描述說 「幫我想想怎麼驗收」、「工程做完了要測什麼」,也應觸發此 skill。 這個 skill 輸入 PRD / AC,輸出結構化測試案例;不寫 PRD、不寫程式碼,只負責「怎麼驗證」。 接力關係:enterprise-prd-writer / prd-writer 產出 AC → 本 skill 把 AC 展開成測試案例 → QA 據以執行。PRD 的每條 Given/When/Then 是輸入,測試案例是輸出。
npx skills add https://github.com/skinnerlee1225/enterprise-prd-toolkit --skill test-case-writer
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.
Take skinnerlee1225/test-case-writer 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.