Total 46,178 skills
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Ultra-lightweight channel for feature workflows: No need to write design docs, checklists, or conduct phased reviews. Let AI write code directly as it normally would, but before it starts, tell it where the CodeStable knowledge base in the project is and how to search it. This way, the code it writes will have fewer pitfalls and be more consistent with project conventions. Trigger scenarios: Users say "fast mode", "fastforward", "skip all those steps", "just start coding", "help me make xxx" and the requirement is too small to go through the design process.
Discussion entry when ideas are still vague — first conduct triage through 1-2 rounds of dialogue to determine which downstream process this discussion should eventually go to: if the idea is clear enough, proceed directly to feature-design; if the direction of a small requirement is set, continue the discussion within the feature and document it in `{slug}-brainstorm.md`; if a large requirement cannot fit into a single feature, hand it over to roadmap for decomposition. The role of AI is a thinking partner, not a recorder — dig out the real problem the user wants to solve, proactively evaluate when the user brings a solution, and propose alternative directions when necessary. Trigger scenarios: when the user says "I have an idea that's not clear yet", "Let's brainstorm first", "I want to do something but it's still vague", "Let's talk about this area", "The function direction is still undecided", or when the user comes with a specific solution but wants to hear other ideas first. Bugs (go to issue) and refactoring (go to refactor) are not handled here.
Issue Workflow Stage 1 — Convert the user's problem into a reproducible, traceable {slug}-report.md through conversation. The AI only asks "what you saw, how to reproduce it, what should happen" here, and does not guess the root cause for the user (that's Stage 2's responsibility). Meanwhile, this stage is the only official decision point for choosing between the fast track and standard path: Based on the user's description, first review the relevant code; if the root cause can be identified at a glance and the required changes are minor, directly inform the user to take the fast track. Trigger scenarios: The user says "file an issue", "record this bug", "I found a problem". This is the starting point of the issue workflow with no pre-dependencies.
Ultra-lightweight channel for refactor processes - used when changes are clearly too small to go through the full scan → design → apply three-stage workflow. AI directly identifies 1-3 low-risk optimization points, confirms with the user once, modifies in-place using classic methods, and validates itself by running tests. No scan checklist, no design documentation, no multi-step human verification required. Trigger scenarios: User says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip the extra steps", and the scope of changes is clearly localized to a single function / single component with test coverage for self-validation.
When developing new features, follow this sub-process — take the vague idea of "add X capability" through to the acceptance closure, with solution documents archived so that both AI and users can later check the original thinking and decision rationale. Trigger scenarios are focused on adding new capabilities ("develop new feature", "add X", "implement XX"), and do not handle bugs in existing code. This skill only acts as a router, deciding which sub-skill to trigger next among brainstorm / design / fastforward / implement / acceptance based on existing artifacts.
Phase 3 of the issue workflow —— Fix code precisely according to confirmed root causes and solutions, verify the results, and document it in {slug}-fix-note.md. This is the final stage of the issue workflow —— no verification closure means the workflow is incomplete. Two entry points: the standard path is triggered from cs-issue-analyze (with existing {slug}-analysis.md), and the fast track is triggered directly from cs-issue-report (without {slug}-analysis.md, as the root cause was identified by AI through code reading during the report phase). Trigger scenarios: User says "Start fixing the bug", "Fix according to the analysis", "Start modifying the code". During the fix, only modify the files specified in the solution; do not make incidental optimizations or introduce new abstractions —— these actions will cause the scope to expand to an untraceable extent.
Break down a requirement that is "too large to be implemented as a single feature" into a list of sub-features with dependencies and statuses, and place it in the independent `codestable/roadmap/{slug}/` directory — serving as the seed and scheduling basis for subsequent multiple feature processes. Two modes: new (draft a new roadmap from a large requirement), update (refresh an existing roadmap: add items, modify dependencies, reorder, mark as drop). Division of labor with requirements / architecture — those two record "what the system is now", while the roadmap records "what we plan to do next". Trigger scenarios: Users say "I want an X system", "Help me break down this requirement", "Schedule this large requirement", "Create a roadmap", or it is found during the feature-design phase that the requirement is too large to fit into a single feature.
One-stop skill for the project architecture center — draft new architecture documents, refresh existing ones, or conduct an architecture health check. Automatically determine the mode based on user input: `new` (draft)/ `update` (refresh to latest code status)/ `check` (review without modification, generate issue list). The `check` mode has three sub-objectives: consistency within a single feature design, alignment between design and code, and consistency among multiple documents under `codestable/architecture/`. Single-target rule — only modify one document or check one target at a time. Trigger scenarios: User says "fill in an architecture doc", "draft an architecture document", "refresh the architecture directory", "write down this module structure", "conduct an architecture check", "is the design internally consistent?", "does the plan match the code?", "are there conflicts among several documents in the architecture folder?", or when an architecture action is required before proceeding during the feature-design / feature-acceptance / implement phases.
Follow this sub-process when fixing bugs — turn the verbal description of "problem found" into a closed loop from verification to repair, leaving three documents: problem report, root cause analysis, and repair record. This process adds a buffer between "seeing the problem" and "starting to modify code" to avoid common pitfalls: the problem description in your mind disappears after the fix, you only fix the surface without analyzing the root cause, the scope of repair expands and cannot be traced, and you don't know if the fix is correct without verification after modification. This skill only acts as a router, deciding which of report / analyze / fix to proceed with based on existing artifacts. For simple problems that can be identified at a glance, a fast track will be taken, skipping the two middle steps and only retaining the fix-note.
This skill bridges the current host coding agent (Claude Code, Codex, or Gemini CLI) to IM platforms (Telegram, Discord, Feishu/Lark, QQ, or WeChat). Use for: setting up, starting, stopping, or diagnosing the IM bridge daemon; forwarding agent replies to a messaging app. Trigger on: "link-to-im", "start bridge", "stop bridge", "bridge status", "消息推送", "消息转发", "桥接", "连上飞书", "手机上看claude", "启动后台服务", "诊断", "查看日志", "启动桥接", "停止桥接", "配置", or any mention of IM bridge management. Subcommands: setup, start, stop, status, logs, reconfigure, doctor. Do NOT use for: building standalone bots, webhook integrations, or coding with IM platform SDKs — those are regular programming tasks.
Skyline 组件开发技能。涵盖 scroll-view 及其增强模式（列表/嵌套滚动）、swiper 高级特性、表单组件、图片/文本组件、半屏可拖拽组件、共享元素动画等。适用于需要开发滚动列表、轮播、表单输入、页面过渡动画等场景。
Creates or updates software localizations/translations. Use when the user wants to translate a project to a new language, add a new locale, create translations, localize strings, or work with i18n/l10n files. Handles any project type (React, Vue, iOS, Android, Rails, Django, .NET, etc.) by auto-detecting the localization framework.