Loading...
Loading...
Found 5,097 Skills
Initializes and maintains architecture artifacts with handoff-first context loading, lazy scoped updates, and compact JSON handoff output for workflow-driven invocations.
Configures Depot-managed GitHub Actions runners as a drop-in replacement for GitHub-hosted runners. Use when setting up or migrating GitHub Actions workflows to use Depot runners, choosing runner sizes (CPU/RAM), configuring runs-on labels, setting up ARM or Windows or macOS runners, troubleshooting GitHub Actions runner issues, configuring egress filtering, using Depot Cache with GitHub Actions, or running Dagger/Dependabot on Depot runners. Also use when the user mentions depot-ubuntu, depot-windows, depot-macos runner labels, or asks about faster/cheaper GitHub Actions runners.
Use this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improving tool selection accuracy, answer quality, reducing costs, or fixing issues where the agent gives wrong/incomplete responses. Evaluates agents systematically using MLflow evaluation with datasets, scorers, and tracing. Covers end-to-end evaluation workflow or individual components (tracing setup, dataset creation, scorer definition, evaluation execution).
Use when working with Python projects that use uv for dependency management, virtual environments, project initialization, or package publishing. Covers setup, workflows, and best practices for uv-based projects.
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.
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
ASCII diagram patterns for architecture, workflows, file trees, and data visualizations. Use when creating terminal-rendered diagrams, box-drawing layouts, progress bars, swimlanes, or blast radius visualizations.
Extract and analyze Agentforce session tracing data from Salesforce Data 360. Supports high-volume extraction (1-10M records/day), Polars-based analysis, and debugging workflows for agent sessions.
Эксперт по автоматизации маркетинга. Используй для настройки HubSpot, Marketo, email sequences, lead scoring и workflows.
Use this when you need to initialize a new Spec Pack in the AI SDLC workflow of this repository (create a three-digit numbered branch and the `.aisdlc/specs/{num}-{short-name}` directory), or when you are unsure about input parsing, short name rules, UTF-8 BOM file path parameter passing, script invocation methods, or output artifacts when executing `spec-init`.
PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.
Migrate existing Python projects to uv from pip, Poetry, Pipenv, or Conda. Learn how to convert dependency files, preserve development environment setup, validate the migration, and plan team rollout. Use when converting legacy projects to modern uv tooling, consolidating different package managers, or standardizing Python development workflows across teams.