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Found 6,689 Skills
Microsoft Teams bots and AI agents - Claude/OpenAI, Adaptive Cards, Graph API
Configure LLM models and providers for Letta agents and servers. Use when setting model handles, adjusting temperature/tokens, configuring provider-specific settings, setting up BYOK providers, or configuring self-hosted deployments with environment variables.
Guides the agent through running and configuring ASGI servers (Uvicorn, Granian, Hypercorn) for Python web applications. Triggered when users say "run a FastAPI app", "configure uvicorn", "set up ASGI server", "deploy with uvicorn", "configure workers", "set up SSL/TLS", "run development server", "configure hot reload", or mention ASGI server, production deployment, server configuration, uvicorn, granian, or hypercorn.
Guides the agent through Python project management with uv, the fast Rust-based package and project manager. Triggered when users say "create a Python project", "init a Python project with uv", "add a dependency", "manage Python packages", "sync dependencies", "lock dependencies", "run a Python script", "set up pyproject.toml", or mention uv, package management, virtual environments, or Python project initialization.
Run blameless post-mortems & retrospectives and produce a Post-mortems & Retrospectives Pack (brief + agenda, facts/timeline, contributing factors + root causes, decisions + action tracker, kill criteria, learning dissemination plan). Use for postmortem, post-mortem, retrospective, retro, after action review, lessons learned. Category: Leadership.
Design a lightweight set of named, templated “Golden Rituals” (team operating cadence) and produce a Team Rituals Pack (ritual inventory, ritual specs + agendas, onboarding primer, rollout + iteration plan). Use for team rituals, operating cadence, meeting templates, team operating system, golden rituals. Category: Hiring & Teams.
AI-powered browser automation using Stagehand v3 and Claude. Use when building self-healing tests, AI agents, dynamic web automation, or when traditional selectors break frequently due to UI changes.
Uncertainty-aware non-linear reasoning system with recursive subagent orchestration. Triggers for complex reasoning, research, multi-domain synthesis, or when explicit commands `/nlr`, `/reason`, `/think-deep` are used. Integrates think skill (reasoning), agent-core skill (acting), and MCP tools (infranodus, exa, scholar-gateway) in recursive think→act→observe loops. Uses coding sandbox for execution validation and maintains deliberate noisiness via NoisyGraph scaffold. Supports `/compact` mode for abbreviated outputs and `/semantic` mode for rich exploration.
TWD test writing context — teaches AI agents how to write correct TWD (Test While Developing) in-browser tests. Use this when writing, reviewing, or modifying TWD test files (*.twd.test.ts).
Optimize LLM prompts, tools, and agents in Opik using standardized optimizer workflows (prompt optimization, tool optimization, and parameter tuning), dataset/metric wiring, and result interpretation.
Use this agent when you need a final review pass to ensure code changes are as simple and minimal as possible. This agent should be invoked after implementation is complete but before finalizing changes, to identify opportunities for simplification, remove unnecessary complexity, and ensure adherence to YAGNI principles. Examples: <example>Context: The user has just implemented a new feature and wants to ensure it's as simple as possible. user: "I've finished implementing the user authentication system" assistant: "Great! Let me review the implementation for simplicity and minimalism using the code-simplicity-reviewer agent" <commentary>Since implementation is complete, use the code-simplicity-reviewer agent to identify simplification opportunities.</commentary></example> <example>Context: The user has written complex business logic and wants to simplify it. user: "I think this order processing logic might be overly complex" assistant: "I'll use the code-simplicity-reviewer agent to analyze the complexity...
Pre-ship audit checklist for Ethereum dApps built with Scaffold-ETH 2. Give this to a separate reviewer agent (or fresh context) AFTER the build is complete. Covers only the bugs AI agents actually ship — validated by baseline testing against stock LLMs.