io.github.BuilderIO/agent-native/design-templates

Find, save, copy, and adapt Design templates. Use when the user references a template, a prior design, or wants a reusable starting point.

io.github.TanStack/table/api-not-found

Diagnose missing TanStack Table v9 exports, options, state slices, and instance methods. Load before inventing an API when code sees a type error, undefined feature method, absent object key, adapter mismatch, or v8-shaped example.

io.github.TanStack/table/typescript

Preserve TanStack Table v9 inference with createColumnHelper, columns(), tableOptions, tableFeatures, and metaHelper. Load for ColumnDef errors, reusable tables, typed meta, named registries, or unnecessary manual feature generics.

io.github.mastra-ai/mastra/react-best-practices

React performance optimization guidelines from Mastra Engineering. This skill should be used when writing, reviewing, or refactoring React code to ensure optimal performance patterns. Triggers on tasks involving React components, data fetching, bundle optimization, or performance improvements.

io.github.PostHog/posthog/setting-up-a-custom-rest-source

Connect an arbitrary REST API to the PostHog data warehouse as a Custom source by authoring a JSON manifest, with no per-source code. Use when the user points at an API that has no built-in PostHog connector — "import data from this REST API", "sync my internal API", "connect this API from its docs", "build a custom data warehouse source" — and gives a docs URL or a natural-language description of the endpoints. Walks through drafting the RESTAPIConfig manifest (auth — bearer, API key, HTTP basic, or OAuth2 client credentials / refresh token — pagination, record path, incremental cursor, parent/child fan-out), validating it, test-reading live rows to verify the field mappings, and creating the source. If the API already has a native PostHog connector, use setting-up-a-data-warehouse-source instead — this skill checks the connector registry first and only handles APIs with no native connector.

io.github.PostHog/posthog/diagnosing-stacktrace-symbolication

Help users debug PostHog Error Tracking stack-trace symbolication for any supported platform — JavaScript/TypeScript web, React Native (Hermes), Android (Proguard / R8), or iOS / macOS (dSYM). The PostHog symbol-set lookup flow is universal across platforms; build-tool and artifact details live in per-platform references (JavaScript is fleshed out, others come as we encounter them). Use when stack frames stay minified or obfuscated after symbols are uploaded, PostHog symbol sets show last_used but frames are not readable, chunk IDs or dSYM UUIDs do not match, "Token not found" appears, uploaded source maps / dSYMs / Proguard mappings look empty, or bundler / symbol-upload configuration needs troubleshooting.

io.github.PostHog/posthog/designing-email-templates

Author, save, and edit email templates in the PostHog workflows library — compose email design JSON with Liquid personalization and create and round-trip-edit templates over MCP. Use when asked to design, build, update, or fix an email template for workflows, broadcasts, or campaigns.

io.github.boshu2/agentops/automation-shape-routing

Front door for agent automation: choose inline, bounded fanout, reusable skill/workflow/gate, persistent agent-native workers, or explicit Gas City. Triggers: "build automation", "which orchestration shape", "should this use NTM".

io.github.boshu2/agentops/automation-shape-routing

Front door for agent automation: choose

io.github.boshu2/agentops/automation-shape-routing

Front door for agent automation: choose inline, bounded fanout, reusable skill/workflow/gate, persistent agent-native workers, or explicit Gas City. Triggers: "build automation", "which orchestration shape", "should this use NTM".

io.github.gmh5225/awesome-game-security/mobile-security

Guide for Android and iOS game security, reversing, and anti-cheat-adjacent platform research. Use this skill when working with APK or IPA analysis, IL2CPP mobile titles, Frida, Zygisk or Magisk, jailbreak or root detection bypass, Android kernel modules, emulator detection, or mobile anti-cheat systems.

io.github.microsoft/skills-for-fabric/sqldw-consumption-cli

Execute read-only T-SQL queries against Fabric Data Warehouse, Lakehouse SQL Endpoints, and Mirrored Databases via CLI. Default skill for any lakehouse data query (row counts, SELECT, filtering, aggregation) unless the user explicitly requests PySpark or Spark DataFrames. Use when the user wants to: (1) query warehouse/lakehouse data, (2) count rows or explore lakehouse tables, (3) discover schemas/columns, (4) generate T-SQL scripts, (5) monitor SQL performance, (6) export results to CSV/JSON. For a Fabric notebook cell (%%sql or other notebook magics), use `spark-authoring-cli`, not this skill. Triggers: "warehouse", "SQL query", "T-SQL", "query warehouse", "show warehouse tables", "show lakehouse tables", "query lakehouse", "lakehouse table", "how many rows", "count rows", "SQL endpoint", "describe warehouse schema", "generate T-SQL script", "warehouse performance", "export SQL data", "connect to warehouse", "lakehouse data", "explore lakehouse".

io.github.labring/FastGPT/api-development

FastGPT API 开发规范。重点强调使用 zod schema 定义入参和出参,在 API 文档中声明路由信息,编写对应的 OpenAPI 文档,以及在 API 路由中使用 schema.parse 进行验证。

io.github.QwenLM/qwen-code/review

Review changed code for correctness, security, code quality, and performance. Use when the user asks to review code changes, a PR, or specific files. Invoke with `/review`, `/review <pr-number>`, `/review <file-path>`, or `/review <pr-number> --comment` to post inline comments on the PR. Add `--effort low|medium|high` to trade depth for speed (defaults to high for PRs, medium for local changes).

io.github.EveryInc/compound-engineering-plugin/ce-doc-review

Review requirements, plans, or specs with role-specific lenses. Use when the user wants to improve an existing planning document.

io.github.BTMuli/TeyvatGuide/typescript-standards

Write and review TypeScript and Vue code using TeyvatGuide's ESLint, Prettier, type declaration, const-enum, runtime-value, and TSDoc conventions. Use when changing .ts, .d.ts, or .vue files, especially types, enums, exported APIs, and Vue state.

io.github.asgeirtj/system_prompts_leaks/code-review

Review the current diff for correctness bugs and reuse/simplification/efficiency cleanups at the given effort level (low/medium: fewer, high-confidence findings; high→max: broader coverage, may include uncertain findings; ultra: deep multi-agent review in the cloud). Pass --comment to post findings as inline PR comments, or --fix to apply the findings to the working tree after the review.

io.github.asgeirtj/system_prompts_leaks/design-sync

Push a React design system to claude.ai/design. This runs a converter that bundles the real component code (from Storybook or a bare package) and uploads it. Use when the user runs /design-sync or says "sync my design system to Claude Design".

io.github.rommapp/romm/frontend-i18n

Internationalization for the RomM frontend (both v1 and v2). Use whenever adding, renaming, or removing any user-visible string / translation key under frontend/src/locales/. Covers the en_US-is-source rule, the requirement to add every new key to ALL locale directories in the same change, namespace layout, and the check_i18n_locales.py validator enforced in CI. Trigger on any change to frontend/src/locales/**.

io.github.worldwonderer/oh-story-claudecode/browser-cdp

Use this skill when you need to control a Chrome browser via CDP (Chrome DevTools Protocol) to reuse existing login sessions. Covers: launching Chrome in debug mode, opening URLs, waiting for page load, evaluating JavaScript, taking snapshots, and extracting auth tokens. Trigger phrases: browser automation, CDP, agent-browser, 浏览器操作, 操作浏览器, Chrome CDP, 复用登录态, extract token from browser.

io.github.dotnet/maui/review-test-failures

Classifies PR CI/test failures as likely PR-caused or unrelated, compares against base-branch baseline, and emits an overall merge-readiness verdict. Uses gathered GitHub/AzDO/Helix context and the shared MAUI CI facts.

io.github.microsoft/ai-agents-for-beginners/local-ai-agents

Bumuo ng mga local-first AI agents na tumatakbo nang buong-buo sa isang developer workstation gamit ang Microsoft Foundry Local at Qwen function-calling models. Saklaw nito ang Small Language Models (SLMs), ang OpenAI-compatible na lokal na endpoint, sandboxed local tools, lokal na RAG gamit ang Chroma, lokal na MCP servers, hybrid cloud/local routing, at ang privacy/cost/offline trade-offs. Batay sa Lesson 17 ng AI Agents for Beginners. GAMITIN PARA SA: pagpapatakbo ng agent nang lokal, offline agent, on-device agent, Foundry Local, Qwen function calling, local tool calling, lokal na RAG, Chroma vector database, lokal na MCP server, privacy-preserving agent, hybrid local at cloud agent, small language model agent, engineering assistant sa aking makina. HUWAG GAMITIN PARA SA: pag-deploy ng mga agents sa cloud nang malakihan (gamitin ang deploying-scalable-agents / Lesson 16), paggawa ng iyong unang agent concept (Lesson 01), Foundry (cloud) hosted agents, GPU cluster / server-side inference provisioning.

io.github.microsoft/ai-agents-for-beginners/deploying-scalable-agents

Dalhin ang isang gumaganang prototype ng agent sa isang scalable, observable na production deployment sa Microsoft Foundry. Saklaw nito ang mga deployment pattern (client-hosted, hosted agents, agent workflows), ang lifecycle ng agent, model routing, response caching, evaluation gates, human-in-the-loop approval, observability gamit ang OpenTelemetry, cost optimisation, at smoke-testing ng mga deployed na agent gamit ang AI Smoke Test action. Batay sa Lesson 16 ng AI Agents for Beginners. GAMITIN PARA SA: pag-deploy ng agent sa production, pag-scale ng agent, Microsoft Foundry hosted agent, Foundry Agent Service, model routing, response caching, evaluation gate, release gate, human approval workflow, agent observability, agent tracing, agent cost optimisation, smoke test ng hosted agent, production customer support agent. HUWAG GAMITIN PARA SA: pagbuo ng iyong unang agent (simulan sa Lesson 01), pagpapatakbo ng mga agent nang lokal sa device (gamitin ang local-ai-agents / Lesson 17), Azure infrastructure prov

io.github.microsoft/ai-agents-for-beginners/azure-openai-to-responses

Ilipat ang mga Python app mula sa Azure OpenAI Chat Completions papuntang Responses API. Saklaw nito ang pag-migrate ng AzureOpenAI/AsyncAzureOpenAI client sa v1 endpoint, streaming, tools, structured output, multi-turn, EntraID auth, at mga pagsusuri sa compatibility ng modelo. Nakatuon sa Python, para sa Azure OpenAI. GAMITIN PARA SA: pag-migrate sa responses API, paglipat mula sa chat completions, openai responses, pag-upgrade ng openai SDK, migration sa responses API, paglipat mula completions sa responses, gpt-5 migration, azure openai python migration, chat completions papuntang responses, AzureOpenAI papuntang OpenAI client, python azure openai upgrade. HUWAG GAMITIN PARA SA: paggawa ng mga bagong app mula sa simula (simulan direkta sa responses), Node/TypeScript/C#/Java/Go migrations (Python lang ang kasanayang ito), Azure infrastructure setup (gumamit ng azure-prepare), pag-deploy ng mga modelo (gumamit ng microsoft-foundry).