Skills
99,064 packaged capabilities and playbooks for agents. Install any of them with one command.
Development
Apache Commons best-practice patterns, distilled from official documentation. Covers Commons Lang3 (the many faces of StringUtils null checks, isEmpty vs isBlank, migrating from Validate throwing NullPointerException), Commons IO (the IOUtils.toString large-file trap, the FileUtils.lineIterator line-by-line read pattern, FilenameUtils.normalize path normalization), and Commons Collections4 (CollectionUtils.union/intersection/subtract set operations). Corrects common LLM misuse: confusing StringUtils.isBlank vs isEmpty, IOUtils.toString causing OOM on large files, not knowing the LineIterator line-by-line pattern, and using the lang package name instead of lang3.
Extract explicit and implicit constraints (compliance, security, hosting, tooling, stakeholder, scope, and external-dependency boundaries) from a project's documentation, then build or update a canonical CONSTRAINTS.md. Spawns one subagent per source document to flag externally-imposed boundaries with evidence citations and confidence ratings, then correlates, deduplicates, and organizes the results by category before writing them into CONSTRAINTS.md. Use this skill whenever a user mentions \"CONSTRAINTS.md\", \"extract constraints\", \"find our constraints\", \"document constraints\", \"compliance constraints\", \"what limits this project\", \"synthesize constraints\", or wants to capture externally-imposed boundaries (legal, security, compliance, stakeholder, vendor) that shape what a project can build and how. Always prefer this skill over ad-hoc constraint documentation.
Generate a project-local skill that formally verifies the code where a bug costs the most and tests reach the least, in any language, with whichever verification tool fits. Use for /create-formal-verification-skill, “model-check this race”, “prove this invariant”, or when concurrency, retries, state machines, parsers, or unsafe code need more than tests.
Strip AI-generated slop from a codebase, product, and prose. Code slop — console statements, `any` types, unused imports, commented-out code, redundant comments, needless defensive try-catch on trusted paths, over-nesting. Product slop (with --product) — marketing-filler copy, generic AI phrasing, default-shadcn look, unstyled loading/error states, dead buttons and half-wired flows. UI slop (`ui`) runs a project-derived design-system primitive pass. Prose slop (`prose`) cuts AI tells from writing. Can scope to the current branch's diff or sweep the whole tree. Use when asked to clean up AI-generated code, unslop writing, remove slop, or make an app feel finished before shipping to customers.
Interactive debugging mode that generates hypotheses, instruments code with runtime logs, and iteratively fixes bugs via autonomous reproduce-analyze loops, with human help only as a fallback. Only for hard-to-diagnose bugs; in those cases, remind the user that debug-mode is available, and never proactively activate this skill
Use Desktop Commander MCP (typically tools like `mcp__desktop-commander__*`) for local files, precise edits, search, and long-running processes on the machine. Use it when the task requires direct local execution, rather than IDE-only actions or remote platform operations.
Turn Contentstack Developer Hub and Marketplace app ideas into concrete implementations. Choose the right UI location, map the architecture, generate boilerplate-aligned React/TypeScript code, and troubleshoot setup, SDK, manifest, proxy, and publishing issues. Use when a user needs help designing or building a Contentstack Developer Hub or Marketplace app.
Periodically audit a repository's docs for staleness against the implementation: run a cheap mechanical scan (dead source-path references, dead links, leftover DEPRECATED/TBD banners, doc-vs-code freshness gap, git-invisible ignored leftovers, completed-but-undeleted plan files), then dispatch parallel read-only agents to verify only the suspicious docs against source, and finally propose update / delete / migrate-to-ADR dispositions for user approval. Use on a monthly or quarterly docs review, after large refactors or renames, or when asked whether docs are stale.
Look up CE.SDK SvelteKit reference docs, guides, and configuration pages. Use when the user needs CE.SDK docs for SvelteKit — configuration, UI customization, export options, feature guides, or getting-started instructions. Also triggered by "IMG.LY", "CreativeEditor", "CE.SDK", or "cesdk" when the user needs an existing SvelteKit doc page. Not for writing code (use build) or concept explanations (use explain). <example> Context: User asks about SvelteKit configuration user: "How do I configure the editor in SvelteKit?" assistant: "I'll use /imgly-sdk:docs-sveltekit to look up configuration options." </example> <example> Context: User asks about SvelteKit SSR user: "Does CE.SDK work with SvelteKit server-side rendering?" assistant: "Let me use /imgly-sdk:docs-sveltekit to find the relevant documentation." </example>
Advanced type-safe RPC patterns for Electrobun desktop applications. Covers bidirectional main↔webview communication, type safety with TypeScript, error handling and validation, performance optimization, streaming data patterns, batch operations, retry strategies, event-based communication, shared type definitions, RPC middleware, request/response patterns, and complex data synchronization. Use this skill when implementing complex communication between main and webview processes, need type-safe RPC with full IntelliSense, handling large data transfers, implementing real-time updates, building type-safe APIs between processes, debugging RPC issues, optimizing RPC performance, or implementing advanced patterns like streaming, batching, or pub/sub. Triggers include "RPC", "main webview communication", "type-safe RPC", "bidirectional RPC", "RPC performance", "RPC error handling", "shared types", "process communication", or "IPC patterns".
Safely diagnose and fix ESLint errors, warnings, and configuration compatibility issues. Use when the user asks to run lint, explain ESLint errors, perform scoped auto-fixes, or migrate ESLint configuration; prefer the project's locked package manager and versions, pre-check before modifying, and do not automatically download the latest version or bulk-rewrite unrelated source code.
Lints, tests, simulates, and formats Fastly VCL code using the falco tool. Also serves as the authoritative VCL reference via the falco Go source, which implements Fastly's full VCL dialect. Use when validating VCL syntax, running VCL linting, testing VCL locally, simulating VCL request handling, formatting VCL files, writing VCL unit tests with assertions, debugging VCL logic errors, looking up VCL function signatures or variable scopes, understanding VCL subroutine behavior, or running `falco lint`/`falco simulate`/`falco test`/`falco fmt`. Also applies when working with VCL syntax errors, type mismatches in VCL, choosing which VCL subroutine to use, or setting up a local VCL development and testing environment.
Verify that a developer-run feature behaved correctly by analyzing HTTP traffic captured by Fiddler Everywhere. Always use this skill when a developer asks whether their feature's HTTP calls completed correctly, wants to see what requests a feature made, needs to debug a failed API call, is checking traffic after running a feature, wants to confirm what each endpoint returned, or asks whether anything in the traffic looks wrong — even if they don't use the word "verify" or "Fiddler". Summarizes the capture by endpoint and flags likely issues such as failed calls, missing follow-up requests, retries, auth failures, timeouts, and suspicious status-code patterns. Requires Fiddler Everywhere to be running with its MCP server enabled.
Diagnose and fix Flutter text display issues including text overflow, orphaned words, line breaking, truncation, multi-style spans, and text scaling. Use when text clips, leaves dangling single words, overflows containers, or requires rich inline spans; route typography tokens and visual hierarchy to flutter-ui-design and screen-level layout constraints to flutter-responsive-layout.
Use when you need to derive a "page inventory → feature points → business processes → business rules" chain from frontend code with evidence, especially when the project has more than one routing entry point, complex dynamic routes/permissions/backend menus, and the team tends to speculate or miss evidence links.
Invoke when the user is preparing for game release, needs a launch checklist, store submission guidance, go/no-go decision framework, or day-one patch planning. Covers Steam, itch.io, Epic, and console submission pipelines. Triggers on: "launch", "release", "store submission", "go/no-go", "day-one patch", "launch readiness". Do NOT invoke for sprint planning (use game-sprint-plan) or code review (use game-code-review). Part of the AlterLab GameForge collection.
Use when a Git merge or rebase produces code conflicts, especially when AI-automated conflict resolution is error-prone (picking the wrong side, losing a refactor, reverting to an older version) and semantic analysis plus logic verification is needed. Also applies when a multi-round rebase stops repeatedly and conflict files need to be aggregated across rounds. Triggers — 「解冲突」「处理冲突」「git-conflict-resolve」「解决 merge 冲突」「解决 rebase 冲突」「冲突解决」 / conflict resolve, resolve merge conflict, resolve rebase conflict.
Go concurrency patterns for high-throughput web applications including worker pools, rate limiting, race detection, and safe shared state management. Use when implementing background task processing, rate limiters, or concurrent request handling.
Guides iOS app development with Swift including SwiftUI views, UIKit view controllers, navigation, async/await networking, Core Data persistence, Xcode project configuration, and App Store submission. Use when the user asks about iOS Swift development, needs to create iOS applications, implement SwiftUI or UIKit components, or configure Xcode signing and TestFlight.
Guide for llama.cpp, the C/C++ LLM inference framework by ggml-org. Covers the C API (llama.h), GGUF format, quantization (Q4_K_M, Q8_0, IQ4_XS), CMake builds, GPU backends (CUDA, Vulkan, Metal, ROCm), HTTP server with OpenAI-compatible API, embeddings, grammar constraints, function calling, LoRA, speculative decoding, multimodal, and UE5 integration. Use when: llama.cpp, GGUF models, local LLM inference, llama.h, llama-server, quantizing, ggml, building/linking llama.cpp, GPU acceleration, llama.cpp embeddings, grammar/JSON output, llama.cpp in Unreal Engine, llama_* API functions, GGUF format, converting HuggingFace to GGUF, or comparing with vLLM/Ollama/TensorRT-LLM.
Skill for Lombok annotation usage rules. Covers @Data/@Builder/@Slf4j combination rules, the @EqualsAndHashCode(callSuper=true) inheritance pitfall, combination with Jackson/@Builder/@Jacksonized, resolving conflicts with MyBatis no-arg constructors, @Value immutable objects, @With object copying, and @SuperBuilder inheriting a Builder. Corrects the most common Lombok misuses by LLMs: not writing callSuper, omitting @Jacksonized, Builder conflicting with inheritance, and loss of @Builder.Default defaults.
Use when writing MATLAB functions with arguments blocks — repeating arguments (arguments (Repeating)), .?ClassName property import in constructors, name-value forwarding with namedargs2cell, or migrating from inputParser or validateattributes. Also when reviewing signatures for implicit-conversion pitfalls (size reshaping, class coercion, computed defaults), or when restricting, constraining, or validating function inputs — scalar vs vector enforcement, type rejection, size checking. Also when asked to harden inputs, make a function more robust, tighten input checking, or rewrite for safer input acceptance — even without "validation" or "arguments block" wording. Triggers on: arguments block, mustBe validators, name-value arguments, varargin, inputParser, nargin/narginchk, restrict input, type checking, scalar constraint, harden inputs, defensive programming. Not for: App Designer callbacks, Simulink mask parameters, class inheritance, or runtime validation outside function or property declarations.
Use Mergify merge queue to queue/dequeue PRs, to monitor and inspect the queue, and to diagnose a dequeued PR — whether it is queued, why it was dequeued, where its CI failure is, and what to do next. ALWAYS use this skill when queuing or dequeuing a PR in the Mergify merge queue, checking its status, finding out why Mergify dequeued a PR, pausing/unpausing the Mergify merge queue, or debugging a merge the Mergify queue did not make. Triggers on mergify queue, @mergifyio queue, @mergifyio dequeue, Mergify merge queue, Mergify queue status, why did Mergify dequeue my PR, Mergify dequeue reason, Mergify queue pause, Mergify batch, Mergify bisecting, CHECKS_FAILED, PULL_REQUEST_UPDATED.
Use when you need a runnable PyTorch training repo for a medical-imaging task (segmentation, classification, detection, synthesis, self-supervised, or fine-tuning a pretrained backbone). Emits a patient-level seed-locked split, train/evaluate scripts, config and a Methods stub.
Write Python code in n8n Code nodes. Use when writing Python in n8n, using _input/_json/_node syntax, working with standard library, or need to understand Python limitations in n8n Code nodes. Use this skill when the user specifically requests Python for an n8n Code node. Note — JavaScript is recommended for 95% of use cases — only use Python when the user explicitly prefers it or the task requires Python-specific standard library capabilities (regex, hashlib, statistics). EXCEPTION — for Python in the AI-agent-callable Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode), use the n8n-code-tool skill instead (input is _query, return must be a string).
Validate n8n expression syntax and fix common errors. Use when writing n8n expressions, using {{}} syntax, accessing $json/$node variables, troubleshooting expression errors, mapping data between nodes, or referencing webhook data in workflows. Use this skill whenever configuring node fields that reference data from previous nodes — expressions are how n8n passes data between nodes, and getting the syntax wrong is the most common source of workflow errors. Also use when asked whether a complex expression hurts performance.
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. Use 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.
Integrate OnboardJS into React projects for building user onboarding flows. Use when: (1) Setting up OnboardJS in a React/Next.js project (2) Creating multi-step onboarding, wizards, or guided flows (3) Implementing conditional navigation, data persistence, or step validation (4) Working with OnboardingProvider, useOnboarding hook, or step components Triggers: "onboarding", "onboardjs", "wizard flow", "user onboarding", "guided tour", "multi-step form"
Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser through the `orca` CLI. Use when the user says "$orca-cli", "Orca worktree", "child worktree", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "handoff" / "handover" / "give this to another agent", "Orca browser", "orca artifacts", or "share skills". Prefer it over raw git worktree, ad hoc PTYs, or Computer Use when Orca state is involved. Use Computer Use only when a visible window needs GUI control that a CLI, filesystem, or API cannot do.
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.