creating-prompts
Creates GitHub Copilot prompt files (`.prompt.md`) for VS Code. Use when building reusable workflow starters that route work to the right agent, collect the right inputs, and ship with install-ready templates, examples, and validation guidance.
creating-custom-agents
Creates GitHub Copilot custom agents (`.agent.md`) for VS Code. Use when defining a specialized agent role, selecting a minimal toolset, referencing supporting skills, or shipping install-ready agent examples with clear boundaries and collaboration rules.
code-review
Performs a quick, lightweight review of a small diff or single file, giving concise feedback on correctness, readability, tests, and obvious risks. Use when the user asks for a fast sanity-check review of a small change. For test-automation suites, architectural refactors, security-sensitive paths, or multi-file reviews, use the code-review-advanced skill instead.
designing-functional-tests
Designs risk-based functional test plans, manual test cases, regression slices, and automation handoff packs from requirements, URLs, or exploratory notes. Use when preparing manual QA coverage before automation, turning feature descriptions into scenario catalogs, or converting exploratory findings into structured test assets.
code-review-advanced
Performs evidence-driven code review for pull requests, legacy modules, and quality-critical changes. Use when reviewing complex or multi-file changes, test automation suites, architectural refactors, or hot paths that need analysis of correctness, maintainability, security, performance, test quality, and operability risks. Provides structured feedback with severity-ranked findings, actionable recommendations, and clear rationale. For a fast sanity check of a small diff or single file, use the code-review skill instead.
auditing-accessibility
Performs webpage and user-flow accessibility audits with WCAG 2.2 guidance, manual verification checklists, prioritized remediation output, and stakeholder-ready summaries. Use when auditing accessibility on a URL, triaging suspected a11y issues, or producing technical findings with practical next steps.
creating-hooks
Creates GitHub Copilot hooks for VS Code using `hooks.json`, supporting scripts, and companion docs. Use when automating deterministic checks, pre/post tool policies, or reusable hook packs that need safe defaults, observability, and clear installation guidance.
api-playwright-test-developer
Writes and reviews API automation tests with Playwright Test, covering setup/teardown, assertions, data management, and hybrid API+UI flows. Use when creating backend API tests, contract checks, data-driven API coverage, API+UI hybrid workflows, or reviewing existing Playwright API suites.
analyzing-regression-scope
Analyzes diffs, changed files, hotfixes, and release candidates to identify where regression risk spreads and what must be retested first. Use when scoping retest after a change, reviewing QA impact for a pull request, or building a minimal confidence suite for release validation.
creating-instructions
Creates GitHub Copilot instruction files for VS Code, including repository guidance and scoped `.instructions.md` rules. Use when encoding project conventions, choosing `applyTo` patterns, or shipping install-ready instruction examples with rationale and guardrails.
designing-test-data
Designs realistic, boundary-heavy, and role-aware test data packs for manual and automated testing. Use when a feature needs deliberate inputs and fixtures before execution, when edge-case values keep being improvised, or when automation needs stable example data with setup notes.
creating-skills
Creates GitHub Copilot skills with reusable workflows, companion resources, and validation gates. Use when packaging repeatable expertise into a `SKILL.md` folder, deciding what belongs in the skill body versus resources, or producing install-ready skill examples for a team or collection.
requirements-test-coverage-mapper
Maps requirements (PRD, user stories, acceptance criteria) to test coverage via a Requirements Traceability Matrix, exposing coverage gaps, risks, test levels, prioritization, and automation candidates. Use when mapping requirements to tests, checking coverage completeness for a PRD or user story, finding missing acceptance criteria, or building a risk-based regression strategy.
tech-debt-analysis
Analyzes technical debt in codebases, test suites, architecture, dependencies, and delivery workflows using observable signals. Use when auditing repository health, explaining slow delivery or flaky tests, prioritizing refactoring, or building an evidence-based remediation roadmap with risk, effort, and ROI. Use when user asks for technical debt analysis, repository audit, or refactor planning.
verifying-acceptance-criteria
Compares implementation evidence against acceptance criteria and shows what is met, partial, missing, or untestable. Use when checking feature readiness, preparing QA sign-off, or turning criteria into a concrete verification matrix without inventing missing behavior.
reporting-bugs
Transforms rough tester notes, screenshots, console output, or observed behavior into reproducible defect reports with severity, evidence, and follow-up guidance. Use when logging bugs, triaging intermittent issues, or rewriting vague defect notes into developer-ready reports.
prd-generator
Produces production-ready Product Requirements Documents (PRDs) for software systems and AI-powered features, with clear problem framing, measurable outcomes, scoped functionality, testable requirements, and explicit risks. Use when the user wants to write a PRD, define requirements, plan a feature, or turn a vague product idea into an implementation-ready specification.
static-code-analysis-typescript
Creates, reviews, and modernizes static code analysis setups for Node.js and TypeScript repositories, covering ESLint flat config, typescript-eslint, tsconfig, Prettier, import sorting, Husky, lint-staged, package.json quality scripts, and CI quality gates. Use when setting up or auditing linting, formatting, type-checking, commit hooks, or GitHub Actions quality checks in a TypeScript project.
request-analyzer
Analyze incoming user requests to detect intent, request type (design/validate/debug/document), complexity level, and identify vague requirements or buzzwords that need clarification. Use when cto-orchestrator receives new requests that need classification before routing to specialist agents.
validation-report-generator
Generate structured 8-section validation reports with verdict (GOOD/BAD/NEEDS MAJOR WORK), strengths, critical flaws, blindspots, and concrete path forward. Use after strategic-cto-mentor has completed validation analysis and needs to produce final deliverable.
tech-stack-recommender
Recommend technology stacks based on project requirements, team expertise, and constraints. Use when selecting frameworks, languages, databases, and infrastructure for new projects.
scalability-advisor
Guidance for scaling systems from startup to enterprise scale. Use when planning for growth, diagnosing bottlenecks, or designing systems that need to handle 10x-1000x current load.
roadmap-generator
Generate phased implementation roadmaps with Epic/Story/Task breakdown, effort estimates, and validation checkpoints. Use when cto-architect needs to create actionable technical roadmaps from architecture designs.
ml-cv-specialist
Deep expertise in ML/CV model selection, training pipelines, and inference architecture. Use when designing machine learning systems, computer vision pipelines, or AI-powered features.
delegation-prompt-crafter
Transform clarified user requests into structured delegation prompts optimized for specialist agents (cto-architect, strategic-cto-mentor, cv-ml-architect). Use after clarification is complete, before routing to specialist agents. Ensures agents receive complete context for effective work.
cost-estimator
Infrastructure and development cost estimation for technical projects. Use when planning budgets, evaluating build vs buy decisions, or projecting TCO for architecture choices.
architecture-pattern-selector
Recommend architecture patterns (monolith, microservices, serverless, modular monolith) based on scale, team size, and constraints. Use when cto-architect needs to select the right architectural approach for a new system or migration.
clarification-protocol
Generate targeted clarifying questions (2-3 max) that challenge vague requirements and extract missing context. Use after request-analyzer identifies clarification needs, before routing to specialist agents. Helps cto-orchestrator avoid delegating unclear requirements.
antipattern-detector
Detect common technical and organizational anti-patterns in proposals, architectures, and plans. Use when strategic-cto-mentor needs to identify red flags before they become problems.
assumption-challenger
Identify and challenge implicit assumptions in plans, proposals, and technical decisions. Use when strategic-cto-mentor needs to surface hidden assumptions and wishful thinking before they become costly mistakes.
react-router-framework-mode
Build full-stack React applications using React Router's framework mode. Use when configuring routes, working with loaders and actions, handling forms, handling navigation, pending/optimistic UI, error boundaries, or working with react-router.config.ts or other react router conventions.
react-router-data-mode
Build React applications using React Router's data mode with createBrowserRouter and RouterProvider. Use when working with route objects, loaders, actions, Form, useFetcher, or pending/optimistic UI without the Vite plugin.
react-router-declarative-mode
Build React applications using React Router's declarative mode with BrowserRouter. Use when configuring routes with JSX, navigating with Link/NavLink, or reading URL params and search params without data loaders or actions.
dora
Query codebase using `dora` CLI for code intelligence, symbol definitions, dependencies, and architectural analysis
toon
Token-Oriented Object Notation is a compact, human-readable encoding of the JSON data model that minimizes tokens and makes structure easy for models to follow. It's intended for LLM input as a drop-in, lossless representation of your existing JSON.
text-truncator
智能截断文本，保持内容的完整性和语义连贯性。适用于长文本预处理、确保文本不超过指定长度限制
knowledge-query
专注于竖屏短剧知识库查询和信息检索，提供专业知识服务。适用于查询剧本桥段、高能情节、创作技巧、商业运营等专业知识
web-search
使用联网搜索获取最新市场信息和行业动态。适用于获取竖屏短剧市场趋势、热门题材分析、成功案例研究
novel-evaluator
严格细致判断与评分故事文本，从市场潜力、创新属性、内容亮点维度分析质量。适用于小说初筛选、多维度评估打分
novel-summarizer
阅读理解小说文本，总结成流畅的故事大纲。适用于小说初筛选、生成500-800字故事大纲
novel-truncator
智能截断文本，保持内容完整性。适用于小说文本预处理、确保文本不超过指定长度限制
score-analyzer
分析多轮评估结果评分数据，统计各项指标，计算评级等级。适用于分析评分趋势、计算S/A/B评级
output-formatter
整合智能体输出结果为结构化最终输出，支持多种格式。适用于整合分析报告、生成结构化报告
result-integrator
整合多情点分析结果为综合报告，通过去重、分类、排序、总结生成高质量分析。适用于整合多分析源、生成统一报告
series-analyzer
分析已播剧集，包括信息获取、拉片分析、五元素分析及联网搜索。适用于深度分析剧集创作技法、学习情节设计
detailed-plot-analyzer
基于大情节点，深入分析并生成详细情节点描述及情节发展说明。适用于细化故事大纲、指导剧本写作、分析情节内在逻辑
drama-analyzer
分析故事文本，提炼主要情节点并分析戏剧功能。适用于分析小说、剧本大纲、故事梗概等文本，识别关键转折点和情感节点
plot-keypoints
梳理故事主线，提炼并按发展阶段排列主要情节点。适用于快速掌握故事结构、制作大纲及剧本改编结构梳理
plot-points-analyzer
分析故事情节点，识别关键情节与转折点。适用于深度分析情节结构、评估情节发展有效性
story-five-elements
全面分析故事五元素：题材类型、故事梗概、人物小传、人物关系、大情节点。适用于深度分析故事、剧本改编准备、故事开发文档制作
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