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Found 5,665 Skills
Configure and operate Codemagic-hosted CodePush for React Native iOS and Android apps, including native plugin wiring, deployment key/server URL setup, Codemagic CI integration, and OTA release lifecycle (release, promote, patch, rollback). Use when requests mention CodePush, codepush, OTA updates, @code-push-next/react-native-code-push, @codemagic/code-push-cli, codepush.pro, deployment keys, or staged iOS/Android rollout workflows.
Jira integration. Manage project management and ticketing data, records, and workflows. Use when the user wants to interact with Jira data.
Asana integration. Manage project management and ticketing data, records, and workflows. Use when the user wants to interact with Asana data.
Enforces a 'Document-then-Execute' workflow. Use when an agent needs to run shell commands, execute tests, build projects, or perform any task that should favor established task runners (Makefile, npm run) and be logged to .cmds-by-agents/ for auditability.
Interactive model selection workflow with paginated navigation. Use when users want to select a model interactively - guides them through provider selection then model selection using the question tool with pagination support for large lists.
Guides structured 4-stage experiment execution with attempt budgets and gate conditions: Stage 1 initial implementation (reproduce baseline), Stage 2 hyperparameter tuning, Stage 3 proposed method validation, Stage 4 ablation study. Integrates with evo-memory (load prior strategies, trigger IVE/ESE) and experiment-craft (5-step diagnostic on failure). Use when: user has a planned experiment, needs to reproduce baselines, organize experiment workflow, or systematically validate a method. Do NOT use for debugging a specific experiment failure (use experiment-craft) or designing which experiments to run (use paper-planning).
Expert guidance for building production-grade AI agents and workflows using Pydantic AI (the `pydantic_ai` Python library). Use this skill whenever the user is: writing, debugging, or reviewing any Pydantic AI code; asking how to build AI agents in Python with Pydantic; asking about Agent, RunContext, tools, dependencies, structured outputs, streaming, multi-agent patterns, MCP integration, or testing with Pydantic AI; or migrating from LangChain/LlamaIndex to Pydantic AI. Trigger even for vague requests like "help me build an AI agent in Python" or "how do I add tools to my LLM app" — Pydantic AI is very likely what they need.
Expert guide for creating GitHub Copilot customization files in VS Code: custom instructions (.instructions.md), prompt files (.prompt.md), custom agents (.agent.md), agent skills (SKILL.md), hooks (JSON), and agent plugins. Use this skill whenever the user asks about customizing Copilot behavior, creating reusable AI workflows, writing copilot-instructions.md, building custom chat agents, automating Copilot tasks with prompt files, or setting up agent skills and hooks in VS Code. Also trigger when the user asks which Copilot customization type to use for a given scenario — always start with the decision matrix below.
Full research pipeline: Workflow 1 (idea discovery) → implementation → Workflow 2 (auto review loop). Goes from a broad research direction all the way to a submission-ready paper. Use when user says "全流程", "full pipeline", "从找idea到投稿", "end-to-end research", or wants the complete autonomous research lifecycle.
React Native and Expo patterns for building performant mobile apps. Covers list performance, animations with Reanimated, navigation, UI patterns, state management, platform-specific code, and Expo workflows. Use when building or reviewing React Native code. Triggers: 'react native', 'expo', 'mobile app', 'react native performance', 'flatlist', 'reanimated', 'expo router', 'mobile development', 'ios app', 'android app'.
Use when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?"
Use when generating a Terraform provider from an OpenAPI spec with Speakeasy. Covers entity annotations, CRUD mapping, type inference, workflow configuration, and publishing. Triggers on "terraform provider", "generate terraform", "create terraform provider", "CRUD mapping", "x-speakeasy-entity", "terraform resource", "terraform registry".