Skills
100,344 packaged capabilities and playbooks for agents. Install any of them with one command.
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Expert in building Telegram Mini Apps (TWA) — web apps that run inside Telegram with a native-like experience. Covers the TON ecosystem, Telegram Web App API, payments, user authentication, and building viral mini apps that monetize. Use when: telegram mini app, TWA, telegram web app, TON app, mini app
When the user wants to build or improve a sales bot's ability to estimate deal timelines based on conversation patterns. Also use when the user mentions "close prediction," "deal timeline," "sales cycle estimation," "forecast timing," or "deal velocity."
Retrieve chemical compound data from PubChem and ChEMBL with disambiguation, cross-referencing, and stereochemistry handling. Use for resolving compound names to SMILES/InChI/CID/ChEMBL IDs (including OPSIN deterministic IUPAC-name-to-structure parsing), fetching molecular properties, distinguishing isomers/stereo forms, and cross-validating identity across databases. Always use English compound names; flags ambiguous queries (e.g., Vitamin D has multiple forms).
Use when you need to apply Java concurrency best practices—including thread safety fundamentals, ExecutorService thread pool management, concurrent design patterns like Producer-Consumer, asynchronous programming with CompletableFuture, immutability and safe publication, deadlock avoidance, virtual threads, structured concurrency, scoped values, backpressure, cancellation discipline, and observability for concurrent systems. Trigger for requests such as reviewing Java code for concurrency or thread safety, fixing race conditions, choosing ExecutorService or virtual threads, improving synchronization and shared mutable state handling, or applying structured concurrency for related Java subtasks. Part of Plinth Toolkit.
Comprehensive Contentful REST API guide. Covers Content Management API (CMA) for creating/updating content, Content Delivery API (CDA) for fetching published content, Preview API, Images API, and GraphQL API. All examples use curl/HTTP — language-agnostic.
Build, test, publish, invoke, schedule, and update Railcode managed agents with the Railcode CLI. Use when creating an organization or personal managed agent, editing an agent manifest (JSON or YAML), running a draft or saved agent, investigating a run, managing its cron schedule, running it from Slack (@Railcode $agent), pairing it with a companion app, processing files in its sandbox, or acting through a connector one person owns (their Gmail, Slack, Granola, ...). Do not use for static Railcode apps, in-app LLM tool loops (llm.generate({ tools }) — see create-railcode-app), or general organization administration.
Audit cryptography implementation — algorithm choice, key sizes, KDF parameters, IV/nonce handling, signature verification, randomness, TLS configuration, and key rotation. Deeper than owasp-audit A04. Use when the user mentions 'crypto review,' 'cryptography audit,' 'encryption review,' 'KDF,' 'PBKDF2,' 'Argon2,' 'bcrypt cost,' 'IV reuse,' 'nonce reuse,' 'AES mode,' 'AES-GCM,' 'AES-ECB,' 'signature verification,' 'TLS configuration,' 'cipher suites,' 'key rotation,' 'libsodium,' 'BoringSSL,' or 'is this crypto right.'
Databricks SQL (DBSQL) advanced features and SQL warehouse capabilities. This skill MUST be invoked when the user mentions: "DBSQL", "Databricks SQL", "SQL warehouse", "SQL scripting", "stored procedure", "CALL procedure", "materialized view", "CREATE MATERIALIZED VIEW", "pipe syntax", "|>", "geospatial", "H3", "ST_", "spatial SQL", "collation", "COLLATE", "ai_query", "ai_classify", "ai_extract", "ai_gen", "AI function", "http_request", "remote_query", "read_files", "Lakehouse Federation", "recursive CTE", "WITH RECURSIVE", "multi-statement transaction", "temp table", "temporary view", "pipe operator". SHOULD also invoke when the user asks about SQL best practices, data modeling patterns, or advanced SQL features on Databricks
Extract the functional DNA from existing works (TV, film, books, plays). Use when adapting a source work, when analyzing what makes something work, when creating trope maps for reuse, or when you need to separate structural necessity from stylistic choice.
Expert patterns for Godot AutoLoad (singleton) architecture including global state management, scene transitions, signal-based communication, dependency injection, autoload initialization order, and anti-patterns to avoid. Use for game managers, save systems, audio controllers, or cross-scene resources. Trigger keywords: AutoLoad, singleton, GameManager, SceneTransitioner, SaveManager, global_state, autoload_order, signal_bus, dependency_injection.
For end-to-end generation and acceptance of React / HiUI pages, from refining requirements onward. Use to generate and review pages from vague product requirements, check HiUI pages before testing, conduct an experience walkthrough after page generation, or close the loop from requirements through implementation to UX acceptance. Orchestrates hiui-refine, hiui-design, and ux-walkthrough: requirementGate, generationInputGate, and uxGate control requirement confirmation, page-generation input confirmation, engineering acceptance, tiered UX acceptance, before/after screenshots, fix closure, and report output
A standard S0 prerequisite skill for larger page workflows such as `hiui-page-workflow`, focused on refining requirements before generating B2B back-office and HiUI pages. Turns vague or abstract back-office, admin, operations, configuration, and approval-flow requirements into actionable product plans, MVP scope, user flows, business rules, traceable page lists, product PRDs, global generation context, page-level prompts, and HiUI handoff packages. Use to clarify back-office product ideas, turn rough requirements into a PRD or product plan, break down list/detail/edit/configuration work areas, define roles and permissions, data permissions, state machines, and audit rules, and, as needed, fill in permission matrices, state transition tables, field dictionaries, exception and audit matrices, bulk/import/export specifications, and legacy-system upgrade and release strategies. It also provides B2B product expertise, including business value analysis, prioritization, trade-offs, multi-tenant/version/provisioning models, master data and system boundaries, anti-pattern detection, and risk alerts—continually turning vague B2B requirements into actionable inputs. For requirements in an existing project or repository, it also refines them in context using the repository’s pages, modules, APIs, types, and documentation.
jscodeshift codemod development best practices from Facebook/Meta. This skill should be used when writing, reviewing, or debugging jscodeshift codemods. Triggers on tasks involving AST transformation, code migration, automated refactoring, or codemod development
Comprehensive market analyst skill that orchestrates all Octagon stock performance and market data skills. Use when conducting stock analysis, creating market reports, evaluating valuations, comparing sectors, or performing technical and sentiment analysis
When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' or 'monetization.' This skill covers pricing research, tier structure, and packaging strategy.
Plan and execute a brand transformation — from diagnosis to new brand definition to rollout. Use when the user says "rebrand", "rebranding", "brand refresh", "update the brand", "modernize the brand", "our brand is outdated", "we've outgrown our brand", "the brand needs to change", "brand transformation", "pivot the brand", "we're changing the brand", "the old brand doesn't fit anymore", or when a brand has evolved in direction, audience, or market position and needs its identity to catch up
Use when automating SAP BW query inspection, InfoProvider metadata reads (characteristics, key figures), metadata-verified specification review, unsaved draft preparation, or human-confirmed query draft population through Eclipse or HANA Studio with BW Modeling Tools.
Testing best practices with React Testing Library and Vitest. Use when: (1) working on .test.tsx, .test.ts, .spec.tsx, or .spec.ts files; (2) writing or refactoring component tests; (3) tasks include keywords such as "test", "testing", "vitest", "RTL", "getByRole", "userEvent", "waitFor", or "expect"; (4) writing tests for asynchronous logic or user interactions
Plan, conduct, and analyze UX research using proven methodologies. Use when planning user research, writing interview scripts, creating test plans, recruiting participants, analyzing qualitative data, or synthesizing findings into actionable insights. Covers generative, evaluative, and continuous discovery research with specific frameworks, scoring rubrics, and templates
Use the Bailian CLI (`bl`) to complete the full “data → fine-tuning → export → deployment → invocation” workflow, or skip training and deploy a base model directly. Supports fine-tuning text models (SFT/DPO/CPT), audio TTS models (CosyVoice), image generation models (Wan2.7), and video generation models (Wan i2v/kf2v). Covers dataset validation/upload, creating fine-tuning jobs, waiting for training, exporting the best checkpoint, creating inference deployments, waiting for readiness, and providing invocation examples. Activate this skill when the user mentions “training a model,” “fine-tuning,” “fine-tune,” “finetune,” “deploying a model,” “launching a model,” “running/invoking a fine-tuned model,” “training an inference model,” “continued pretraining,” “LoRA/SFT/DPO training,” “speech synthesis model,” “TTS fine-tuning,” “CosyVoice,” “voice cloning,” “image generation fine-tuning,” “text-to-image,” “image-to-image,” “Wan2.7,” “image model training,” “video generation fine-tuning,” “image-to-video,” “first-frame-to-video,” “first-and-last-frame,” “kf2v,” “i2v,” “Wan video,” or “video effects training” on Bailian / DashScope / Alibaba Cloud Model Studio. Use it even if the user does not explicitly say “use bl,” as long as they intend to train or deploy on Bailian; do not assemble commands yourself.
Create fast, high-impact 15-30 second brand and product marketing videos from an official company website, verified brand sources, or user-uploaded product imagery. Use for launch films, website motion videos, AI/SaaS demos, product promos, and Vibe Motion/Remotion productions that require exact logos, authentic imagery, English-first copy, product-feature storytelling, strong visual impact, smooth transitions, and deterministic frame-based animation.
Identify candidate stocks in batches with mature breakout patterns, healthy price-volume structures, and favorable catalysts, then output priorities, trigger conditions, and invalidation boundaries. Suitable for short- to medium-term stock selection, pre-market candidate pool preparation, and screening potential leaders during sector rotation
Manage scheduled tasks using the openclaw cron CLI. Trigger when the user needs recurring reminders, scheduled tasks, background checks, or scheduled agent tasks. Keywords: schedule, daily/weekly/hourly/every minute/every second, reminder, schedule, remind, every, cron, scheduled task, run later, delayed execution, reservation, plan, alarm, countdown, in X minutes, in X seconds, at what time
Authors Apache Airflow DAGs declaratively from dag-factory YAML configs. Use when building DAGs declaratively from YAML via dag-factory; creating/editing dag-factory templates/YAML configs,reating/editing dag-factory YAML configs, defaults, dynamic tasks, datasets, or callbacks; or validating dag-factory configurations; upgrading or re-pinning dag-factory.
Configures and manages Depot CI, a drop-in replacement for GitHub Actions that runs workflows entirely within Depot. Use when migrating GitHub Actions workflows to Depot CI, running `depot ci migrate`, managing Depot CI secrets and variables, running workflows with `depot ci run`, debugging Depot CI runs with `depot ci run list`, `depot ci status`, `depot ci logs`, `depot ci diagnose`, or `depot ci ssh`, inspecting test results with `depot tests` or run artifacts with `depot ci artifacts`, checking workflow compatibility, running Depot CI on Entire repositories, or understanding Depot CI capabilities. Also use when the user mentions .depot/ directory, depot ci commands, or asks about running GitHub Actions workflows on Depot's infrastructure without GitHub-hosted runners.
Diagnoses why a session recording is missing or was not captured. Use when a user asks why a session has no replay, why recordings aren't appearing, or wants to troubleshoot session replay capture issues for a specific session ID or across their project. Covers SDK diagnostic signals, project settings, sampling, triggers, ad blockers, and quota/billing scenarios.
Drafts a design document section-by-section using the concepts brief from egm-brainstorm (or user notes). This is the second step in the Elephant-Goldfish (EGM) feature flow. Use when you are ready to write a design doc after aligning on requirements + solution.
Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs
Comprehensive Expo React Native feature development guide. This skill should be used when building mobile app screens, navigation, data fetching, authentication, deep linking, or native UX patterns with Expo. Triggers on tasks involving Expo Router, React Native components, mobile forms, or app configuration.
Expert blueprint for TileMapLayer and TileSet systems for efficient 2D level design. Covers terrain autotiling, physics layers, custom data, navigation integration, and runtime manipulation. Use when building grid-based levels OR implementing destructible tiles. Keywords TileMapLayer, TileSet, terrain, autotiling, atlas, physics layer, custom data.
Use this skill when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO, and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Use for cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without a local GPU setup.
Use when designing or building native macOS applications with SwiftUI or AppKit. Triggers on menu bar structure, keyboard shortcuts, multi-window behavior, Liquid Glass design system, macOS Tahoe/Sequoia, sidebar navigation, toolbar design, app icons, SF Symbols, or making an app feel like a “good Mac citizen”
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.