Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Development
Autonomously completes a confirmed milestone by reconciling existing work, coordinating work-item delivery and the configured milestone release, and closing the verified milestone. Use when the user runs /milestone-rush or asks to complete one exact, confirmed milestone, including selecting it after /roadmap-review.
Helps users run multiple concurrent mirrord sessions from a single mirrord-up.yaml (compose-style multi-service local debugging). Use when the user mentions mirrord up, mirrord-up.yaml, mirrord up init, debugging several related microservices together, or managing multiple mirrord sessions' lifecycle in one command.
Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.
Application monitoring and observability setup for Python/React projects. Use when configuring logging, metrics collection, health checks, alerting rules, or dashboard creation. Covers structured logging with structlog, Prometheus metrics for FastAPI, health check endpoints, alert threshold design, Grafana dashboard patterns, error tracking with Sentry, and uptime monitoring. Does NOT cover incident response procedures (use incident-response) or deployment (use deployment-pipeline).
Guide for modernizing and migrating MSBuild project files to SDK-style format. USE FOR: converting legacy .csproj/.vbproj with verbose XML to SDK-style, migrating packages.config to PackageReference, removing Properties/AssemblyInfo.cs in favor of auto-generation, eliminating explicit Compile Include lists via implicit globbing, consolidating shared settings into Directory.Build.props. Indicators of legacy projects: ToolsVersion attribute, an Import of Microsoft.CSharp.targets via $(MSBuildToolsPath), .csproj files over 50 lines for simple projects. DO NOT USE FOR: projects already in SDK-style format, non-.NET build systems (npm, Maven, CMake), .NET Framework projects that cannot move to SDK-style
Deploy and consume the Multimodal Embedding Serving microservice — bring it up with setup.sh + docker compose (from a repo clone, or by fetching those same files from GitHub when no clone exists) using the prebuilt intel/multimodal-embedding-serving image, embed text/images/videos over REST on port 9777, choose among 19 models (CLIP/SigLIP/MobileCLIP/CN-CLIP/Blip2/ QwenText), or integrate in-process via the Python SDK wheel. Use when an app needs embeddings for similarity search or retrieval. Not for modifying the service's source — that is multimodal-embedding-serving-dev.
Design n8n AI agents the right way. Use when building or editing any @n8n/n8n-nodes-langchain.* AI node — an AI Agent, LLM chain, Text Classifier, or Information Extractor — and whenever the user mentions AI agents, LLM with tools, tool calling, $fromAI, system prompts, agent memory, sessionId, structured/JSON output, output parser, RAG, vector store, a chat assistant/bot, or human-in-the-loop review. Covers Agent-vs-chain-vs-classifier choice, the model/memory/tools/outputParser slots, tool names/descriptions as prompt, structured output with autoFix, memory, RAG, human review, and chat topologies.
Provides expert guidance on Next.js App Router navigation, prefetching behavior, Link component configuration, and client-side state preservation. Use when working with Next.js navigation, Link prefetching, Suspense boundaries during navigation, App Router routing, or PageProps typing.
Build, refactor, and architect Angular state with the @ngrx/signals Signal Store. Use whenever the user mentions signalStore, withState, withMethods, withComputed, withHooks, withLinkedState, withFeature, signalStoreFeature, withEntities, rxMethod, signalMethod, patchState, the SignalStore events plugin (withReducer, withEventHandlers), or wants to refactor BehaviorSubject/service-based state to Signal Store. Also use for designing custom store features, request status, optimistic updates, entity collections, and the store/service split in Angular. Do NOT use for @ngrx/store (classic Redux), createReducer/createEffect, or generic RxJS questions unrelated to Signal Store.
Interact with Obsidian vaults using the Obsidian CLI to read, create, search, and manage notes, tasks, properties, and more. Also supports plugin and theme development with commands to reload plugins, run JavaScript, capture errors, take screenshots, and inspect the DOM. This skill MUST be used when the user asks to interact with their Obsidian vault, manage notes, search vault content, perform vault operations from the command line, or develop and debug Obsidian plugins and themes.
Implement Combined post-processing effects (tone mapping, color grading, vignette) in Graphics3D. MUST use when: (1) Adding effect to Combined post-process, (2) User mentions 'Combined post-process' or 'post-processing'. DOES NOT apply to multi-pass effects (bloom, depth-of-field).
Use when analyzing OpenHarmony sysfreeze/appfreeze logs to diagnose process freeze and thread blocking issues. Triggers on SERVICE_BLOCK, THREAD_BLOCK_6S, IPC deadlock, task queue blocking, or when user requests sysfreeze/process stuck analysis.
OpenTelemetry - vendor-neutral observability framework for distributed systems. Provides traces, metrics, and logs with standardized instrumentation and exporters. USE WHEN: user mentions "opentelemetry", "otel", "distributed tracing", "observability", asks about "how to trace microservices", "opentelemetry setup", "jaeger integration", "prometheus metrics" DO NOT USE FOR: Application logging only - use logging skills instead, APM vendor-specific - use vendor docs, Simple monitoring - Prometheus/Grafana may be sufficient
Formulate and implement operations research optimization models—LP, MIP/QP, constraint programming, network flows, assignment, VRP, scheduling, resource allocation, inventory/production planning; heuristics and metaheuristics; sensitivity and infeasibility diagnosis; solver integration (OR-Tools, Gurobi, CPLEX, HiGHS, PuLP, Pyomo); production OR APIs (timeouts, warm starts). Use for operations research, OR engineer, optimization model, linear programming, mixed integer programming, MIP, VRP, vehicle routing, scheduling optimization, OR-Tools, Gurobi, constraint programming, resource allocation optimization, infeasible model, metaheuristic—not ML prediction (data-scientist), SCM strategy without optimization math (supply-chain-manager), WMS features (wms-developer), simulation platforms (simulation-software-engineer), generic backend (senior-software-engineer), dbt/warehouse (analytics-data-engineer).
Main entry point for working with Opper (https://opper.ai), the AI gateway for agents. Use when the user mentions Opper without choosing a surface: "set up Opper", "try Opper", "build with Opper", "migrate to Opper", or "help me with Opper". Explore context and route to opper-mcp for agent-assisted setup, platform operations, and model tests; opper-cli for explicit CLI and shell workflows or launching coding agents through Opper; opper-api for application code (the OpenAI, Anthropic or Google SDKs and agent frameworks on the compat endpoints), raw HTTP, and platform concepts; or opper-multimodal for media, files, and realtime voice. Own setup, verification, and follow-up.
Optimize and compress 3D assets for the web — shrink glTF/GLB models and textures using gltf-transform, gltfpack/meshopt, Draco, and KTX2/Basis, and optionally convert a model to an R3F component with gltfjsx. Use when a model is too heavy, loads slowly, or needs to be web-ready before adding it to a Three.js/R3F scene.
Coordinate an end-to-end Jira ticket workflow from ticket fetch through per-task implementation. Use this skill when the user provides a Jira URL, says "work on ticket PROJECT-123", "resume PROJECT-123", "continue this Jira ticket", "start the Jira workflow", or asks for status on a ticket without naming a specific phase. This top-level coordinator keeps SKILL.md as a routing layer, loads bundled references just in time, and dispatches execution-heavy work to downstream skills or co-located utility subagents.
Central entry point of the afonsoft agent harness. Use when starting a new project, resuming an existing one, planning features/Epics/releases, or running any multi-step agent-driven work. Validates and reconciles SPECs (SDD), audits the codebase and harness for gaps (security, architecture, performance, hygiene), proposes improvements, fragments work into GitHub Issues, delegates implementation/QA/review to specialized skills, and re-validates everything until delivery. Also use to review unapproved SPECs, reconcile open GitHub Issues with code, or run a final gap check before closing a release.
Instrument applications with the OpenTelemetry SDK and prove the telemetry is good by validating it against a local Kopai backend. Use when setting up observability, adding tracing/logging/metrics, deciding what to instrument or which attributes to add, retrofitting OTel into an existing codebase, threading context through call chains, configuring sampling, or when traces/logs/metrics aren't appearing after setup. Also use when users say things like "my traces aren't showing up", "I don't see any data", or "how do I add observability to my app". Do NOT use to investigate existing telemetry for a root cause (use root-cause-analysis), to build dashboards (use create-dashboard), or to instrument LLM and agent calls (use otel-genai-instrumentation).
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
Divide-and-conquer implementation from specs/plans. Decomposes a reference document into independent tasks, assigns each to a builder agent, executes in parallel waves respecting dependencies, then integrates results. Use when you have a spec, PRD, plan, or large feature to implement quickly with parallel execution.
Use when handling BK-CI pipeline variables, such as variable lifecycle, runtime passing, cross-task updates, field extension, and conversion between YAML and internal models. Prefer it when the user wants to change the main variable path rather than ordinary pipeline steps.
Guidance for developing under a projects managed by pixi. Always use when workspace managed by pixi (have pixi.toml or pixi.lock in root directory.) Covers all you should know while developing under a pixi-based project: pixi environment commands (install, run, shell, add, task), multi-environment management (-e flag, features), task configuration in pixi.toml, dependencies (conda vs PyPI), lock files, and development workflows. Helps with environment setup, package management, running tasks, debugging pixi.toml errors, and production deployment patterns.
Use when capturing an idea, drafting a design, or tracking work-in-progress in a repo's plans/ directory — creating or updating a plans/YYYY-MM-DD-topic.md file (including a bug, idea or risk turned up incidentally), asking what plans exist or what to work on next, here or across every repo, choosing or advancing a status, retiring a landed/abandoned plan once its content has a permanent home elsewhere, migrating a repo's legacy monolithic plan file (PLAN.md, DESIGN.md, ...) onto this convention, or auditing AGENTS.md/README.md/docs for planning/status/future-work content that has drifted in and belongs in plans/ instead. Also owns where a plan file may live and what may be written in it: a work, client or employer repo that cannot take a plans/ directory keeps its plans in the store outside every working tree ($PLANS_HOME), routed per repo by config; an idea with no repo yet is filed unscoped and graduated later; and no plan committed to a repo you publish may name a client, employer or internal project.
Write, check, repair and publish a plan page: a project's plans and subject files under its plans directory, rendered by .agents/pstack/plan-page.mjs and rendered as one local HTML page per subject with a local index of every subject, and published to claude.ai at each hand-back for comments and feedback. The page is how planned work hands back to the user. Use before writing or changing a plan, a subject file in <plans>/topics or its page; at every stop that hands back work with a plan, such as a review verdict other than a review-only panel's, a next answer or a playbook's close; before writing or updating a PR body, which renders from the PR's plan, or a comment about your commits on someone else's PR; when a plan page or its claude.ai artifact looks wrong or refuses to render; to republish a page; or to change the page shape or a playbook's page sections.
Build, review, debug, configure, migrate, or plan Playwright browser automation and E2E tests with current docs. Use for @playwright/test, playwright, playwright.config, locators, getByRole, locator.visible, frameLocator, assertions, fixtures, Page Object Model, storageState auth, test locks, retryStrategy, network mocking, HAR, traces, UI Mode, codegen, CI sharding, Docker, APIRequestContext, stories/galleries component testing, accessibility, screenshots, visual comparisons, AbortSignal, and Playwright MCP or CLI agent tooling.
Reviews all comments on the current pull request, evaluates whether each one still needs action, and decides whether to address it or resolve it. Holds remarks written by AI review agents to a stricter evidence bar, because they judge a diff without the context a human reviewer carries. Use when the user asks to triage PR comments, review feedback, resolve review threads, or decide which PR comments still matter.
Use when handling the core modules of the BK-CI Process pipeline, such as pipeline CRUD, build startup, runtime state, engine control, event-driven behavior, and database persistence. Prefer it when the user wants to change the main pipeline path rather than peripheral support modules.
Build a throwaway prototype to flesh out a design before committing to it. Routes between two branches — a runnable terminal app for state/business-logic questions, or several radically different UI variations toggleable from one route. Use when the user wants to prototype, sanity-check a data model or state machine, mock up a UI, explore design options, or says "prototype this", "let me play with it", "try a few designs".
Adds new AI providers to claude-council, configures provider API settings, troubleshoots provider connections, and documents the provider script interface. Covers creating provider shell scripts, setting API keys, and validating connectivity. Triggers on "add provider", "new AI agent", "provider not working", "API configuration", or "extend council".
Progressive Web App development. Service workers, Web App Manifest, offline-first strategies, caching with Workbox, push notifications, and installability. USE WHEN: user mentions "PWA", "Progressive Web App", "service worker", "offline-first", "Web App Manifest", "Workbox", "installable web app", "cache-first", "add to home screen" DO NOT USE FOR: native mobile apps - use `react-native`, `flutter`, `expo`; push notification server-side - use `push-notifications`
PyQt6 UI design assistant that generates and refines modern, professional desktop interfaces using a consistent design system (DESIGN.md tokens). Use this skill whenever the user wants to: build or improve a PyQt6 GUI, write QSS stylesheets, add light/dark theme support, generate sidebar navigation, data tables, forms, cards, modals, or any other PyQt6 component. Also trigger this skill when the user uploads or mentions existing PyQt6 code that needs a "refresh", "redesign", "modern look", or "professional UI". Use even for partial UI tasks like "style my button" or "make a dark sidebar" — any PyQt6 styling task benefits from this skill.
Performs comprehensive code reviews for Python files following PEP 8 and Google Python Style Guide standards. Checks code quality, best practices, security, performance, maintainability, and style compliance. Use when reviewing Python code or when asked to check, audit, or improve Python code quality.
Reviews Rails pull requests, focusing on controller/model conventions, migration safety, query performance, and Rails Way compliance. Covers routing, ActiveRecord, security, caching, and background jobs. Use when reviewing existing Rails code for quality, conducting a PR review, or doing a code review on Ruby on Rails (RoR) code.
Use when upgrading a Rails application from one version to another, assessing upgrade readiness, planning a multi-hop upgrade path, or investigating breaking changes, deprecation warnings, gem compatibility issues, or config.load_defaults transitions between any Rails versions from 5.2 through the latest release.
Runs autonomous loop fetching stories from GitHub Issues. Implements and closes issues as done. Triggers on "loop through my PRDs", "work on my issues", "start the autonomous loop", "implement my PRDs", or requests to work through GitHub issues autonomously.
React form handling patterns and best practices. Covers controlled vs uncontrolled forms, React Hook Form, form validation, complex form patterns, and Server Actions forms. USE WHEN: user mentions "React forms", "controlled inputs", "uncontrolled inputs", "form validation", "multi-step form", asks about "form handling", "form state", "React Hook Form basics" DO NOT USE FOR: React Hook Form with Zod - use `react-hook-form` skill instead, React 19 Server Actions - use `react-19` skill instead, basic input handling - use `react` skill instead
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.