Apply a disciplined engineering workflow to any code change. Use whenever implementing a feature, fixing a bug, or refactoring — before writing code, not after. Walks orient → baseline → smallest change → test → verify → self-review, and enforces language-agnostic hard gates (don't mass-reformat, keep the linter and type-checker clean, keep the build and tests green, make interface changes additive, protect security invariants).
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
You are making a code change. This skill is the execution order; it is
stack-agnostic. Adapt every command to the project's actual toolchain: read the
project's own docs (README, CONTRIBUTING, AGENTS.md/CLAUDE.md, a Makefile or
package scripts) once to learn its build, test, lint, and format commands before
you start.
tasks/lessons.md) and obey it.
Find and read the one doc for the subsystem you're changing, not the whole tree.tasks/todo.md —
files touched, tests to add, risks. Going sideways → stop and re-plan.feat|fix|docs(scope): …).await/blocking call, or read env inside logic → extract a pure decision functionThe same failure surviving two fix attempts means stop: write the finding to your lessons
file, mark the item [BLOCKED], and surface it. Don't thrash.
还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问，或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
Transform saved links, papers, articles, posts, videos, and reference collections into approachable AI teaching artifacts for later study. Use when a user wants to queue learning material, create a readable explanation from a source, teach a paper or post step by step, or run an interactive tutor that validates understanding over multiple sessions.
中文简介正在准备中。当前显示原文说明。
Inspect an unfamiliar repository, turn a focused Markdown behavior scenario into a deterministic test in the repository's native test stack, run it, and preserve traceability between intent and code. Use when asked to add scenario tests, compile acceptance criteria or Given/When/Then Markdown into executable tests, reproduce a user-visible regression, or convert a narrow workflow specification into stable web, API, CLI, desktop, or mobile interaction coverage. Do not use for broad exploratory journeys or agent-judged smoke tests.
中文简介正在准备中。当前显示原文说明。
Create truthful, human-centered marketing campaigns for an app or product, including positioning, channel copy, original artwork, editable layouts, README banners, and selective website integration. Use when asked to make launch materials, promotional artwork, social assets, campaign kits, ads, or marketing content from an existing product; to adapt a visual reference without copying it; or to add approved campaign art to product surfaces. Do not invent claims, fake UI, publish, deploy, or replace product proof without explicit evidence and authorization.
中文简介正在准备中。当前显示原文说明。
Create or update a complete repository skill from a user's idea, including the workflow instructions, references, scripts or assets, agent metadata, skill-card artwork, cinematic banner artwork, README links, discovery metadata, and validation. Use when the user asks to create a new skill, add a skill to this collection, turn a workflow into a reusable skill, or make a skill's documentation and artwork consistent with the repository.
中文简介正在准备中。当前显示原文说明。
Use when the user asks to run or continue an autonomous build: turn a goal into an approved plan, dispatch implementation and review agents, and finish with one pull request. The Lead is a provider-neutral orchestrator that makes decisions but never writes code, edits files, runs commands, or reviews its own work.
中文简介正在准备中。当前显示原文说明。
Provider-neutral deep-research orchestration for brainstorming, technology choices, comparisons, and state-of-the-art surveys. The Research Lead makes scope and decision calls while native subagents scout, search, verify, synthesize, audit, write, and commit every research artifact.
中文简介正在准备中。当前显示原文说明。