Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Development
Use after specify approval is approved to break confirmed outcomes into a traceable implementation checklist. Produces plan.md with sections, seam-firmness test labels, acceptance-criterion traceability, and one bounded review cycle without prescribing private control flow. Do not run unless the specify approval is approved.
Turn a prioritized set of requirements into a committed Pragmatic release plan — themed, sized, and signed. Use when the PM asks to plan a release, define MVP scope, commit a date, build a release charter, or “what goes in this release”. Covers MVP done right, themes, the estimation ladder, the market window, and the scope/schedule/resources change levers. Produces a Release Charter as a Markdown or Word .docx artifact.
Use when building Rails features that handle personal data, adding encryption to models, implementing consent flows, building DSAR endpoints, or adding anonymization/pseudonymization. Also use when reviewing code for compliance with privacy laws like GDPR and LGPD, or when asked about privacy-by-design patterns in Rails
Use when building custom AEO monitoring infrastructure. Covers API access, scraping architecture, legal compliance, and cost estimation for AI search visibility tracking. Reference implementation: TypeScript/Next.js/Supabase stack.
Generate or overhaul a coherent, non-redundant set of AI coding-agent instruction files for a project — a canonical entry file (AGENTS.md) plus a rules directory, wired into the target tool (OpenCode's opencode.json, Cursor's .cursor/rules/*.mdc, CLAUDE.md, or AGENTS.md alone). Built on a library of specialised rule templates selected by detected stack, not by copying a whole profile. Use this whenever the user wants to bootstrap rules for a new project, add rules to an existing one, regenerate rules for a new stack, or complains that AI-generated rule files are spaghetti — overlapping, redundant, contradictory, too vague, ignored by the agent, or inconsistent in depth from one file to the next. Also use when the user asks how to structure AGENTS.md, asks to preserve or migrate a codebase's existing conventions, or wants a repeatable process instead of re-prompting from scratch on every project. — Génère ou refond un ensemble cohérent et non redondant de fichiers d'instructions pour agents IA : un fichier d'entrée canonique (AGENTS.md) plus un répertoire de règles, branchés sur l'outil cible. Construit sur une bibliothèque de gabarits spécialisés choisis selon la stack détectée, plutôt que de copier un profil complet. Utiliser pour initialiser les règles d'un nouveau projet, en ajouter à un projet existant, régénérer les règles pour une nouvelle stack, ou quand les fichiers de règles générés sont spaghetti — redondants, contradictoires, vagues, ignorés par l'agent, ou incohérents en profondeur d'un fichier à l'autre. Utiliser aussi pour structurer AGENTS.md, ou pour donner un processus reproductible au lieu de réexpliquer les conventions à chaque session.
Guide Python design patterns, refactoring, and architecture decisions. Use when deciding whether to add an abstraction, splitting tangled code, choosing composition vs inheritance, reducing coupling, or making Python code easier to test and change.
Design and implement Python tests with pytest, fixtures, mocking, parametrization, and regression coverage. Use when writing tests, setting up a test suite, debugging failing tests, choosing test scope, mocking external dependencies, or deciding what coverage is meaningful.
Call local Grok CLI, Kimi Code CLI, and Claude Code CLI with the strongest current default models and native tools. Use this qiaomu skill workflow when the user wants to run Grok 4.5 for X/web search, image/video generation, research, or multi-tool agent work; run Kimi K3 (1M) for frontend UI/CSS/React/Vue work; run Claude Fable 5, Opus 4.8, or Sonnet 5 for coding/review/refactors; run independent multi-model comparisons concurrently with native stream progress, artifact verification, private logs, cancellation, and failed-job retry; choose between the three CLIs; or wrap non-interactive CLI invocations. Trigger on phrases like "用 grok cli", "用 kimi cli", "grok 搜 X", "kimi 写前端", "qiaomu-model-cli", "调用 grok4.5", "调用 k3 1m", "用 claude code", "用 fable 5", "opus 4.8 改代码", "分别调用三个模型", "多模型横评". Not for generic cloud API registry management (use qiaomu-llm) or OpenCLI site adapters.
Use when user requests translating Qt project localization files (TS files), automating translation workflows, or setting up multilingual support for Qt applications. This skill uses parallel processing with ThreadPoolExecutor to translate TS (Translation Source) files efficiently.
Redux-Saga best practices, patterns, and API guidance for building, testing, and debugging generator-based side-effect middleware in Redux applications. Covers effect creators, fork model, channels, testing with redux-saga-test-plan, concurrency, cancellation, and modern Redux Toolkit integration. Baseline: redux-saga 1.5.1. Triggers on: saga files, redux-saga imports, generator-based middleware, mentions of "saga", "takeEvery", "takeLatest", "fork model", or "channels".
Refactor Express.js/Node.js code to improve maintainability, readability, and adherence to best practices. Transforms callback hell, fat route handlers, and outdated patterns into clean, modern JavaScript/TypeScript code. Applies async/await, controller-service-repository architecture, proper middleware patterns, and ESM modules. Identifies and fixes anti-patterns including blocking event loop, improper error handling, forEach with async callbacks, and memory leaks.
Use when you have a PoC or prototype and want to rebuild it as a production-quality system from scratch. Distills the functional intent and lessons learned from the prototype, discards the implementation, and produces a reforge-seed.md that seeds a greenfield architect session. Do NOT use to improve an existing production system — use architect for that.
Guidance for generating legal chess moves using only regex pattern matching and substitution. This skill applies when implementing chess move generators constrained to regex-only solutions, FEN notation parsing/manipulation, or similar pattern-matching-based board game logic. Use this skill for tasks requiring regex-based state transformations on structured string representations.
This skill should be used when the user asks to "create a replit prompt", "write a prompt for replit", "optimize for replit agent", "prepare instructions for replit", or mentions building something with Replit Agent. Transforms user requirements into optimized, structured prompts that Replit Agent understands and executes accurately with minimal iterations.
Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.
Provides repository design rules and anti-patterns in DDD. Checks naming conventions based on aggregates, method design based on CQS (Command Query Separation), and input/output type constraints. Use when detecting repository design problems during code review, new implementation or refactoring. Target languages: language-agnostic (Java, Kotlin, Scala, TypeScript, Go, Rust, Python and all others). Triggers: starts on repository design related requests such as "review the repository design", "the Repository name is wrong", "the return value of findById", "the repository returns DTOs", "I created a repository based on a table name", "repositories per aggregate", "repository anti-patterns", "repository CQS".
Requirement design workflow - mandatory before any creative development (new features, components, behavior changes, API/DB design): triage, parallel exploration, one-question-at-a-time clarification, adversarial validation and 2-3 option comparison produce a spec, then hand off to writing-plans. Use exploring first while the idea is unsettled; not for pure Q&A, test runs, or no-design-space small fixes (use quick-fix).
Gate 0 of the development cycle. Executes code implementation using the appropriate specialized backend agent based on task content and project language. Handles TDD, coverage, docker-compose/local runtime, basic health/observability verification, and delivery verification inside one backend-owned gate.
Mailgun (Sinch) platform help — developer-first transactional email API and SMTP relay with inbound routing, webhooks, and Mailgun Optimize deliverability tools. Use when Mailgun emails not delivering, DNS records (DKIM/SPF) failing verification, inbound routing not catching messages, webhooks not firing, templates rendering wrong, Mailgun Optimize showing poor inbox placement, or API calls returning errors. Do NOT use for general email deliverability strategy (use /sales-deliverability), cross-platform email marketing (use /sales-email-marketing), or email open/click tracking strategy (use /sales-email-tracking).
Build, review, debug, migrate, or plan Schema.org JSON-LD with Google schema-dts TypeScript types. Use for schema-dts, schema-dts-gen, schema-dts-lib, WithContext, Graph, IdReference, MergeLeafTypes, ProductLeaf and other *Leaf types, WithActionConstraints, implements PersonLeaf classes, JSON-LD script injection, structured data, Organization, WebSite, Product, Offer, FAQPage, Article, BreadcrumbList, react-schemaorg, schema-dts-gen 2.0.1 security fix, and Schema.org v30 typing.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
