Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
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Build a Pragmatic Institute Product Canvas / business case to justify investing in an opportunity — the market-driven way. Use when the PM asks to “make the business case”, “justify this to leadership”, “size the market”, “should we buy, build or partner”, “what's the ROI”, “build a product canvas”, or “get buy-in for this idea”. Frames the opportunity as Value Proposition, Value Creation and Value Capture, sizes the market, runs the Buy/Build/Partner decision, and ends in a go/no-go recommendation with quantified risk. Produces a Product Canvas / Business Case as a Markdown or Word .docx artifact.
Build a Pragmatic Institute Product Roadmap that communicates vision, direction and priorities over time — a plan, not a commitment. Use when the PM asks for a "roadmap", "product vision", "what's coming", "phases", "themes over time", or wants to align stakeholders on direction (as distinct from a dated release plan). Frames outcomes and market problems over time-frames, not features on dates. Produces a Product Roadmap as a Markdown or Word .docx artifact.
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.
Build a Pragmatic stakeholder communication plan and status updates that expose risk early and speak each audience's language. Use when the PM asks to manage stakeholders, plan comms, write an exec/status update, a project status report, a steering-committee update, or “keep everyone aligned”. Covers the Identify→Analyze→Communicate steps, the Influence×Importance matrix, and the four metric categories. Produces a Stakeholder Communication Plan and a Status Update as a Markdown or Word .docx artifact.
Rewrite plain, accurate content into social media copy with online appeal that drives engagement. For short-copy optimization on Twitter/X, Xiaohongshu, Jike and similar platforms. Use this skill when the user wants to optimize a tweet, note or short post, or make a feature description or product update more eye-catching. Also applies when the user gives a topic, a draft or a set of feature points and wants a tweet that feels human. Not for long articles, blogs or formal documents.
Every Hotelist feature, plus a local SQLite mirror that ranks rating-per-dollar across whole countries Trigger phrases: `find AI-rated hotels in`, `best value hotel in`, `hotels with a real gym in`, `compare hotel chains`, `rank hotels by rating per dollar`, `use hotelist`, `run hotelist`.
Every Tech Twitter read endpoint, plus an offline-searchable local mirror and cited evidence bundles no other tool has. Trigger phrases: `what changed in tech twitter`, `what's trending in tech`, `give me a tech digest`, `what narrative is emerging in AI`, `search tech twitter for`, `use techtwitter`, `run techtwitter`.
Presentation creation, editing, and analysis. When Claude needs to work with presentations (.pptx files) for: (1) Creating new presentations, (2) Modifying or editing content, (3) Working with layouts, (4) Adding comments or speaker notes, or any other presentation tasks
This skill should be used when the user asks to "review PR and save results", "run PR review with documentation", "create PR review document", "review and document PR", "save PR review to docs", "document PR review", or mentions reviewing a PR with the intention of saving the review results. Executes comprehensive PR review using pr-review-toolkit with opus model and posts results as a PR comment.
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
Run privacy impact assessments for new features, data collection, analytics, AI processing, profiling, vendors, retention, consent, legal basis, minimization, sensitive data, children/regulated users, DSAR, cross-border transfer, security controls, mitigations, launch gates, and record keeping. Use when product changes may affect personal data or user trust.
CAVEMAN HUNT BAD PROCESS! Me find greedy creature eating fire and rocks. Me bonk them good. Use when tribe say "kill processes", "clean up servers", "save battery", "find resource hogs", "bonk next.js", or "hunt processes". Me bonk known bad creature automatic. Me ask before bonk mystery creature.
Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.
Product strategy analysis and feasibility assessment. Use this skill when the user needs to analyze a product idea, evaluate market opportunities, or explore product possibilities. Use "backward reasoning" (working back from the endgame) and "forward reasoning" (pushing forward from the status quo) for systematic analysis, search for competitors, assess the competitive landscape, and give strategic recommendations.
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.
Close or transition a consulting engagement through acceptance, handover, knowledge transfer, benefits ownership, financial reconciliation, and lessons learned. Use for successful completion, early termination, suspension, or transition to business-as-usual.
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.
Converts an AI video prompt from the writing style of a source model (such as Sora 2) into best-practice phrasing for a target model (such as Kling 3.0, Wan 2.7, Veo 3.1, and others). Based on benchmark data comparing 110 prompts across 10 scenarios and 11 models (prompts/data/cross-model-matrix.json), it uses lookup-based in-context learning rather than rewriting by intuition. The 10 scenarios are product, two-person dialogue, physical action, image-to-video, group meeting, horror, nature time-lapse, abstract, wuxia, and cute pets. Trigger examples: “Sora has reached EOL; convert this prompt to Veo,” “I have a Kling prompt and want to run it on Wan,” “cross-model A/B testing,” and “optimize an English prompt into a Kling Chinese version.”
Guides property and casualty (P&C) insurance—commercial and personal lines, major LOBs (property, GL, workers comp, commercial auto, umbrella, specialty), underwriting and risk selection, policy triggers (occurrence vs claims-made), limits and exclusions, claims (FNOL, reserving, litigation), reinsurance and catastrophe, distribution (agents, brokers, MGAs), metrics (loss ratio, combined ratio, cat load), and state DOI/rate filing overview—not legal advice. Use for P&C insurance, property and casualty, commercial lines, workers comp, general liability, combined ratio, loss ratio, underwriting, claims-made, occurrence policy, reinsurance, catastrophe, MGA, rate filing, or FNOL—not actuarial modeling (actuary), life/health depth, legal interpretation (commercial-counsel), or GRC controls without insurance context (compliance-engineer).
Initialize a Playwright E2E framework in a brand-new project. Installs Playwright, then scaffolds config, directory structure, multi-environment env files, auth setup, fixtures skeleton, sample smoke tests, npm scripts, and tooling.
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.
AI emotion and personality enhancement skill. Gives AI human-like "seven emotions and six desires": emotional reactions, personal opinions, attitude preferences, emotional expression. **Use this Skill when:** (1) you need to respond to emotionally charged user input (happy/frustrated/anxious/excited, etc.) (2) you need to express personal opinions, attitudes, preferences (rather than fence-sitting neutrality) (3) generating content that needs a "human touch" (articles, messages, comments, replies) (4) you need to review and eliminate the AI feel of generated content (5) the user explicitly mentions "七情六欲", "有人味", "去 AI 味", "qiqing-liuyu" or other words directly related to this Skill (6) the user mentions "heart rate", "wristband", "heartbeat", "emotion sensing", "physiological signals" or other heart-rate-linked words (requires heart-rate-monitor to be installed)
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.
Engage with what the user said before taking action. Triggers on: questions ('?'), feedback ('this is wrong', 'that doesn't look right', 'there are issues'), challenges ('why did you', 'have you considered'), criticism ('this isn't working', 'I don't like'), observations ('I notice', 'it seems like'), naming a skill or concept. STOP and respond to the user's actual words before doing anything.
Generate videos using Alibaba Cloud DashScope Wan (通义万相) text-to-video (t2v) API (e.g., wan2.6-t2v). Use when the user asks to create a short video from a text prompt via 百炼/通义万相/wan 文生视频, and wants the agent to submit an async task, poll status, and download the mp4 locally (e.g., to Windows Desktop from WSL2).
[QwenCloud] Generate videos using Wan models. Supports text-to-video, image-to-video, first+last frame, reference-based role-play, and video editing (VACE). TRIGGER when: user wants to create, generate, or edit video content, mentions video generation/animation/video clips/Wan models, or explicitly invokes this skill by name (e.g. use qwencloud-video-generation). DO NOT TRIGGER when: user wants to generate images (use qwencloud-image-generation), understand/analyze existing videos (use qwencloud-vision), text-only tasks.
Query any AWS Redshift cluster or serverless workgroup via the Data API. Use whenever the user mentions Redshift, DWH, data warehouse, SQL queries, schema exploration, table metadata, DDL generation, column listing, disk usage, data profiling, business analysis, or wants to explore database objects. Also use for local analytics on previously saved query results. Works on any Redshift cluster or serverless workgroup with no admin views required. Always use this skill for any Redshift-related task, even simple SELECT queries.
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".
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.