Skills
101,174 packaged capabilities and playbooks for agents. Install any of them with one command.
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Designs the four policy-level settings for a Salesforce Field Service scheduling policy — name, optimization mode (In-Day vs Global), commit mode, and description — and delegates to work rule design when complete. Use this skill when a user wants to design, configure, or set up a Field Service scheduling policy's policy-level settings.
Designs the work rules for a Salesforce Field Service scheduling policy — the hard filters that determine which resources and time slots are eligible for an appointment. Step 2 of the three-part scheduling policy design flow; receives the policy block from sfs-scheduling-policy-designer and delegates to sfs-service-objective-designer when complete. Use this skill when a user wants to design or configure the work rules (hard eligibility filters) for a Field Service scheduling policy.
Use for first principles thinking, or when the user questions an inherited default: "why do we do it this way?", "is this cost really necessary?", "should we copy what competitors do?". Strips analogies and rebuilds from fundamentals. Skip for convention-following checklists.
Implement, debug, or verify Flutter work that must continue or be scheduled after the app leaves the foreground, including OS-scheduled jobs, foreground services, and headless callbacks. Use for persistent background execution; route in-process async or CPU work to dart-concurrency and notification delivery to flutter-notifications.
Use when authoring or modifying a Datex Studio form (configurationTypeId=5, *-form.json suffix) on a branch — transient-input collector, dialog opener, and validate-then-confirm workflow host. Owns the TypeScript-expression encoding for declarative string slots, declarative vs imperative init separation, dialog opener pattern, and confirm-button gating. Triggers: "create a form", "add a field to xxx form", "open a dialog that collects X", "a confirmation dialog with inputs", "validate-then-confirm workflow", "declarative binding is not populating the field", "confirm button always disabled", "dialog outParams are undefined on cancel".
Guide for implementing Dify frontend query and mutation patterns with TanStack Query and oRPC. Trigger when creating or updating contracts in web/contract, wiring router composition, consuming consoleQuery or marketplaceQuery in components or services, deciding whether to call queryOptions()/mutationOptions() directly or extract a helper or use-* hook, configuring oRPC experimental_defaults/default options, handling conditional queries, cache updates/invalidation, mutation error handling, or migrating legacy service calls to contract-first query and mutation helpers.
READ this skill when designing or planning any game system architecture — including combat, skills, AI, UI, multiplayer, narrative, or scene systems. Contains paradigm selection guides (DDD / Data-Driven / Prototype), system-specific design references, and mixing strategies. Works as a domain knowledge plugin alongside workflow skills (OpenSpec, SpecKit) or plan mode of an agent.
Design, inspect, or repair game mechanics, core loops, rules, goals, actions, state, chance, secrets, skills, and emergent dynamics. Use when building gameplay systems, combat, puzzles, progression, simulations, board/card mechanics, or any feature where rules create player behavior.
Invoke when the user asks about sprint planning, milestone tracking, scope management, risk assessment, scheduling, resource allocation, team velocity, or needs production coordination across the development team. Triggers on: "sprint", "milestone", "scope", "risk", "schedule", "resource", "velocity", "deadline", "crunch", "cut list". Do NOT invoke for creative vision (use game-creative-director) or architecture decisions (use game-technical-director). Part of the AlterLab GameForge collection.
Evaluate project scope against timeline and resources. Triggers on: "scope creep", "feature list", "can we fit this in", "timeline pressure", "resource constraints", "cut list", "scope evaluation". Do NOT invoke for sprint planning (use game-sprint-plan) or general project status (use game-producer). Part of the AlterLab GameForge collection.
Analyze gaps by comparing a defined current state with a justified target state, characterizing causes and uncertainty, prioritizing actionable interventions, and producing traceable matrices, roadmaps, and decision records. Use for capability, process, compliance, readiness, maturity, operating-model, or research-evidence gaps. Do not use for a vague list of problems, a standalone root-cause analysis, a generic SWOT, or legal or audit certification advice without a governing standard and qualified owner.
Gate Smart Earn (L2) via gate-cli: Simple Earn, dual products, staking, yield compare, idle-fund ideas, subscribe/redeem with confirmation. Use this skill whenever the user asks about earn APY, flexible or fixed earn, dual investment, staking rewards, positions, or earn subscribe/redeem. Trigger phrases include earn, Simple Earn, dual investment, staking, flexible earn, fixed earn, subscribe earn, redeem earn, auto renew, APY compare.
Generate speech from text using Google Gemini TTS models via scripts/. Use for text-to-speech, audio generation, voice synthesis, multi-speaker conversations, and creating audio content. Supports multiple voices and streaming. Triggers on "text to speech", "TTS", "generate audio", "voice synthesis", "speak this text".
Generates or updates a resumable cold-start handoff package from an in-progress conversation, review, debugging session, or investigation, with transcript materialization, verified structured artifacts, update-mode backups, and bounded review repair. Use when the user says create a handoff doc, save this for later, document what we found, update the resumption file, or prepare a fresh agent to resume without chat history.
Optimize existing blog posts and web content for GEO (Generative Engine Optimization) — AI search visibility on ChatGPT, Perplexity, Claude, and Google AI Overviews. Use whenever a user provides a blog URL or pastes existing content and asks to optimize it for AI search, rewrite for LLM visibility, improve GEO score, make content answer-first, add FAQ sections, restructure headings for AI retrieval, improve citation potential, or audit content for AI readiness. Also triggers on "GEO optimize this", "make this AI-search ready", "rewrite for Perplexity", "optimize for ChatGPT", "optimize for Google AI Overviews", "improve AI visibility", "reformat for AI search", "make this content citation-worthy", "content isn't showing up in AI search", "why isn't my blog cited by AI", "GEO audit", "answer-first rewrite", "restructure for AI", "make my blog AI-friendly", "improve LLM citability". Do NOT trigger for writing new content from scratch — use geo-content for that.
Controls the Ghostty terminal emulator via CLI actions and configuration. Use when managing Ghostty windows, fonts, themes, keybinds, config validation, or debugging terminal configuration. Use for ghostty CLI, terminal config, theme selection, font management.
Use when authoring or modifying a Datex Studio grid (configurationTypeId=3, *-grid.json suffix) on a branch — the densest UI component. Owns the pre-author rows-source decision (owned vs standalone datasource, OData vs flow), the five-location dynamic-filter wiring rule, secondary enrichment datasources, imperative cell API, and the mandatory grid-validator gate after every edit. Triggers: "create a grid", "add a column to xxx grid", "make the grid filterable/sortable by X", "add a toolbar button", "add a filter", "enrich rows with extra data", "empty column", "dynamic filter contract mismatch", "grid renders blank", "tailored/custom grid variants", enrichment-datasource work.
Use when auditing a Datex Studio grid configuration before merge or diagnosing grid rendering/filter/sort/toolbar bugs — the mandatory final gate after grid-creator. Carries grid-specific gotchas the generic component-validator doesn't catch: envelope shape, text-display coercion, five-location dynamic-filter wiring sync, imperative cell API mismatches, and tailored vs custom provenance conformance. Triggers: "audit a grid", "check a grid before merge", "diagnose grid rendering / filter / sort / toolbar bugs", "final gate after grid-creator". For non-grid components, use component-validator.
Build or review animation on plain HTML/CSS/JavaScript sites: GSAP page intros/outros, component show/hide, scroll effects, cross-document View Transitions, bfcache, and fetch/swap navigation with Swup, Barba, or Taxi. Use for first-paint flashes or interrupted navigation, even when GSAP is unnamed. Also covers hidden-content recovery and first-load performance. Not for component frameworks or isolated GSAP API questions.
Gatekeeping Git/PR by classifying change essence and recommending granularity, naming, and strategy; the `ship` recipe also executes PR delivery (create, CI watch, merge, cleanup) with Ask First on merge. Use when PR preparation, commit strategy, or gated PR delivery is needed.
Validate Dockerfiles against best practices for syntax errors, image tagging, package pinning, and shell script issues in RUN commands. Auto-detects hadolint binary or Docker image fallback. Checks project config or falls back to sensible defaults. Use when creating or modifying Dockerfiles, reviewing container images, or catching Dockerfile anti-patterns before building.
Set up and improve Harness engineering for AI agent-friendly codebases (including AGENTS.md, docs/, lint rules, eval systems, project-level prompt engineering). Trigger scenarios: setting up a new/empty project for an AI agent, creating AGENTS.md or CLAUDE.md, questions about Harness engineering, making an agent work more efficiently on a codebase. Also triggers when the user is frustrated or complains about agent quality (e.g. 'the agent always ignores the spec', 'it never follows instructions', 'why does it always get X wrong', 'the agent is broken') — because poor agent output almost always means missing Harness, not a model problem. Covers: context engineering, architectural constraints, multi-agent collaboration, evaluation, long-running task Harness, the agent loop (autonomous operation, verifiers, stop conditions), agent memory (cross-session memory, memory stewardship), and diagnosing agent quality issues.
[Hyper] Use when working on Hono projects or adding Hono into a codebase. Enforces Hono architecture rules for app composition, scalable route modules, middleware, validation, database/ORM boundaries, Drizzle integration, migrations, error handling, OpenAPI/Swagger documentation, testing, and typed RPC boundaries before any code change.
Install Kunpeng DevKit in WebUI mode on Huawei Cloud. Create a Kunpeng (aarch64) ECS via Python SDK with random password, encrypt password via Python KMS SDK, use hcloud CLI for EIP/VPC operations, use Python paramiko SSH (password in process memory only) to install DevKit-All-x.x.x-Linux-Kunpeng.tar.gz, including framework and all plugins (porting/affinity/devtools/debugger/sys_perf/java_perf/sys_diagnosis). Use this skill when the user wants to install DevKit on a new Kunpeng ECS. Trigger: user mentions "DevKit", "Kunpeng DevKit", "install DevKit", "DevKit WebUI", "Kunpeng DevKit", "DevKit-All", "鲲鹏DevKit", "安装DevKit", "鲲鹏开发套件"
Hutool Chinese Java utility library skill. Covers a feature selection matrix against Guava/Apache Commons, quick references for the most common string/collection/date/file/HTTP methods, HttpUtil vs OkHttp selection, and BeanUtil vs MapStruct responsibility split. Use when users need utility methods for Chinese scenarios (pinyin/ID card/phone number validation), HTTP requests, file operations, or encryption/decryption in a Java project. Prevents LLMs from reinventing the wheel instead of using Hutool.
Generate Android and iOS app icon sets from one source image with a bundled Pillow script. Use when Codex needs to create mobile app launcher icons, iOS AppIcon.appiconset assets, Android mipmap icons, adaptive icon foreground/background/XML files, extra square sizes, or rounded-corner icon exports from a logo or artwork file.
Format and submit papers to IEEE journals (Transactions, Journals, Letters, IEEE Access) and IEEE conferences using the IEEEtran LaTeX class or Word templates, covering journal vs conference modes, abstracts and index terms, numbered IEEE reference style, figures and equations, author biographies, page limits and overlength charges, IEEE PDF eXpress, copyright forms, double-blind options and ScholarOne/IEEE Author Portal submission. Use when writing for any IEEE venue, fixing IEEEtran layout issues, or checking IEEE submission compliance.
A professional academic paper image-description feature for scientifically and academically describing figures such as maps, flowcharts, data charts, and conceptual diagrams. Follows the principle that the main text is central and figures provide supporting evidence. Use when the user needs to write an academic description of a figure in the paper’s main text. Not tied to a specific research topic; domain terminology is supplied by the user or project writing guidelines.
Audit a repo against Cloudflare/isitagentready signals for AI agent readiness: robots.txt, llms.txt, Markdown negotiation, MCP/API catalogs, OAuth discovery, WebMCP, and browser-agent usability. Includes explicitly scoped readiness audits; not generic SEO or standalone standards documentation questions.
Audits any landing or service page across 48 checks in 10 categories for LLM/AI discoverability, GEO readiness, content clarity, schema markup, internal linking, freshness signals, and technical crawlability. Produces an overall score out of 100, a per-category score out of 100, pass/warn/fail/ manual counts, and a prioritised fix list — all rendered as a standalone HTML report saved to disk. Use when a user provides a URL and asks to audit it, score it, check its GEO readiness, test its AI discoverability, run a landing page audit, or evaluate it for LLM citation potential. Also trigger on phrases like "audit this page", "score this URL", "check GEO for", "is this page AI-ready", "run a GEO audit", "LLM page check", "how would AI read this page", or "landing page score".
Validate Life Sciences Cloud for Customer Engagement org prerequisites. Use when an admin needs to verify that all required settings, permissions, OWD sharing rules, and feature toggles are correctly configured before deploying Life Sciences Cloud. Checks user profile, permission sets, Life Sciences CE settings, surveys, OWD, inventory, account plans, care plans, Chatter, data protection, multi-currency, state/country picklists, and person accounts. Reports pass/fail for each check with remediation steps. TRIGGER when: user says 'check prerequisites', 'verify org setup for Life Sciences', 'LSC readiness check', 'pre-requisites for Life Sciences Cloud', 'validate org for LSC'. DO NOT TRIGGER when: user wants to automatically enable or configure these settings, or when the user asks for the full end-to-end Life Sciences Cloud setup / orchestration (that is the `life-sciences-fieldsalesrep-coordinate` orchestrator's job — this skill runs only as a standalone prerequisites check).
Use this skill to create and activate a Territory Type, Territory Model, and Territories for Life Sciences Cloud. Trigger when the user says 'set up territories', 'create territory model', 'configure territory hierarchy for Life Sciences', 'territory setup for LSC', or 'create territories for Life Sciences Cloud'. Creates a Geographical territory type, an LSC Territory Model, and a 3-level territory hierarchy (Region, District, Territory). Confirms names with the user, shows a preview, then deploys and activates the model. DO NOT TRIGGER when: user wants to validate prerequisites, assign users to territories, create territory assignment rules, or run the full end-to-end Life Sciences Cloud setup / orchestration (that is the `life-sciences-fieldsalesrep-coordinate` orchestrator's job — this skill runs only as a standalone territory setup).
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.