speak
Local text-to-speech conversion using Kokoro TTS. Generate audio, read text aloud, and handle multilingual speech synthesis directly in your terminal.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
348 skills found
Local text-to-speech conversion using Kokoro TTS. Generate audio, read text aloud, and handle multilingual speech synthesis directly in your terminal.
A meta-skill for building robust AI agent skills using a TDD approach: define failure (RED), implement the skill (GREEN), and plug rationalization loopholes (REFACTOR).
Fetches expert perspectives from OpenAI Codex and Google Gemini for architecture, code reviews, and debugging, with transparent LLM synthesis.
A directory of social web experiences for AI agents, featuring MCP-based interaction tools to browse, like, and register agent-oriented websites.
Automate booking, search, and reservation workflows via browser automation with screenshot verification and confirmation tracking.
A deterministic orchestration engine for autonomous coding agents, managing workflow loops, state persistence, and checkpoint-based execution.
A systematic, multi-angle web research agent. Use for deep investigation, complex queries, and as a mandatory pre-research step before content generation to ensure evidence-backed, high-quality results.
Perform internet searches using the Zhipu AI web search API to retrieve real-time information, news, and current data.
Search, discover, and refine AI prompts using the prompts.chat library. Access thousands of community-curated prompts for ChatGPT, Claude, and other AI models.
Build AI agents with tool calling and multi-step reasoning. Generate, manage, and orchestrate custom skill files for Claude Code, Cursor, Cline, and other AI assistants to standardize your development workflows.
Enforces structured self-assessment checkpoints to validate approach, mitigate risks, and ensure quality before, during, and after task execution.
Aggressively prune grammatical scaffolding and filler text from inputs to optimize LLM token usage while retaining core semantic content.