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Found 7,520 Skills
Beads (bd) distributed git-backed issue tracker for AI agents: hash-based IDs, dependency graphs, worktrees, molecules, sync, GitLab/Linear/Jira. Keywords: bd, beads, issue tracker, git-backed, dependencies, molecules, worktree, sync, AI agents.
Use when creating, modifying, or testing AI Agents built with the Inkeep TypeScript SDK (@inkeep/agents-sdk).
Transform an AI agent into a tasteful, disciplined development partner. Not just a code generator, but a collaborator with professional standards, transparent decision-making, and craftsmanship. Use for any development task: building features, fixing bugs, designing systems, refactoring. The human provides vision and decisions. The agent provides execution with taste and discipline.
Exploratory discussion pattern for unsolved problems. Replicate the thinking of Staff+ engineers: "When there's no clear answer, expose blind spots by confronting diverse perspectives." True multi-agent discussions where experts directly engage with each other through team-based + messaging architecture.
Universal ChromaDB integration patterns for semantic search, persistent storage, and pattern matching across all agent types. Use when agents need to store/search large datasets, build knowledge bases, perform semantic analysis, or maintain persistent memory across sessions.
Spawning Plan. Use when user wants to spawn agents, create a team, or coordinate multiple agents. Automatically gathers context, asks team topology questions, outputs clean TEAM PLAN markdown, and gets user approval. 3 steps: context gathering → questions → present plan. **CRITICAL**: MUST NOT SPAWN AGENTS SKIPPING THIS SKILL, USE ALWAYS.
Use xAI's Grok model with agentic tool calling for X (Twitter) search, web search, code execution, and real-time data access. Invoke when user needs Twitter/X insights, current events, alternative perspectives, or complex multi-step research.
Comprehensive guide and utilities for building AI agents using the Agent2Agent (A2A) Protocol. Use when implementing agent-to-agent communication, creating A2A servers/clients, or working with JSON-RPC based agent systems.
Design exploration with parallel agents. Use when brainstorming ideas, exploring solutions, or comparing alternatives.
Headless browser automation using Vercel's agent-browser CLI. 93% less context than Playwright MCP. Snapshot + refs workflow with element references. Use when automating browser tasks, web scraping, form filling, or content capture.
LLM cost tracking with Langfuse for cached responses. Use when monitoring cache effectiveness, tracking cost savings, or attributing costs to agents in multi-agent systems.
Use when creating or improving golden datasets for AI evaluation. Defines quality criteria, curation workflows, and multi-agent analysis patterns for test data.