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Found 3,437 Skills
Work with the Inpoxia repository's local tools and workflows for CLI usage, GraphMail library changes, and quality checks. Use when tasks involve running or updating `inpoxia` commands, modifying files under `src/inpoxia/**`, validating behavior with `pytest`, or enforcing style/type checks with `ruff` and `pyright`.
Creates system prompts, writes tool descriptions, and structures agent instructions for agentic systems. Use when the user asks to create, generate, or design prompts for AI agents, especially for tool-using agents, planning agents, or autonomous systems. **PROACTIVE ACTIVATION**: Auto-invoke when designing prompts for agents, tools, or agentic workflows in AI projects. **DETECTION**: Check for agent/tool-related code, prompt files, or user mentions of "prompt", "agent", "LLM". **USE CASES**: Designing system prompts, tool descriptions, agent instructions, prompt optimization, reducing hallucinations.
Transform podcast transcripts into multiple content assets—blog posts, social snippets, newsletters, and SEO-optimized landing pages—using systematic repurposing workflows. Use when: Maximizing ROI from podcast episodes; Creating blog content from audio/video; Generating social media posts from long-form content; Building newsletter content from transcripts; Extracting quotes and highlights for promotion
Maintain durable project context in `tasks/context.md` (state, decisions, milestones, gotchas, optional context links), inline during other workflows or standalone for cleanup/backfill. Triggers: update context.md, decision log, record project context, capture high-value reference links that improve context handoff.
Automated test generation, review, and execution for pytest-based projects. Auto-activates on keywords test, coverage, pytest, unittest, integration test, e2e, performance, benchmark, security testing. Routes to specialized testing workflows based on user intent.
Instructions for using the ModelMix Node.js library to interact with multiple AI LLM providers through a unified interface. Use when integrating AI models (OpenAI, Anthropic, Google, Groq, Perplexity, Grok, etc.), chaining models with fallback, getting structured JSON from LLMs, adding MCP tools, streaming responses, or managing multi-provider AI workflows in Node.js.
Scaffold and implement GitHub Apps from existing automation ideas using Probot + @octokit/app. Use when turning scripts, bots, or manual GitHub workflows into a proper GitHub App.
Warehouse Management System testing patterns for inventory operations, pick/pack/ship workflows, wave management, EDI X12/EDIFACT compliance, RF/barcode scanning, and WMS-ERP integration. Use when testing WMS platforms (Blue Yonder, Manhattan, SAP EWM).
Install and configure Vercel Workflow DevKit before it exists in node_modules. Use when the user asks to "install workflow", "set up workflow", "add durable workflows", "configure workflow devkit", or "init workflow" for Next.js, Express, Hono, Fastify, NestJS, Nitro, Nuxt, Astro, SvelteKit, or Vite.
Pulumi CLI command reference for infrastructure deployments. Use when the user asks about "pulumi commands", "deploy with pulumi", "pulumi up", "pulumi preview", "manage pulumi stacks", "pulumi state management", "export/import pulumi state", or needs help with Pulumi CLI operations and workflows.
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, checking workflow compatibility, or understanding Depot CI's current beta limitations. 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. NOTE: Depot CI is currently in beta with limited availability.
Effect-TS (Effect) guidance for TypeScript. Use when building, refactoring, reviewing, or explaining Effect code, especially for: typed error modeling (expected errors vs defects), Context/Layer/Effect.Service dependency wiring, Scope/resource lifecycles, runtime execution boundaries, schema-based decoding, concurrency/scheduling/streams, @effect/platform APIs, Effect AI workflows, and Promise/async migration.