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Found 6,397 Skills
Build AI agents with AWS Bedrock AgentCore. Use when developing agents on AWS infrastructure, creating tool-use patterns, implementing agent orchestration, or integrating with Bedrock models. Triggers on keywords like AgentCore, Bedrock Agent, AWS agent, Lambda tools.
Recommend the right agents and skills for any task. Covers both heavyweight agents (Task tool) and lightweight skills (Skill tool). Triggers on: which agent, which skill, what tool should I use, help me choose, recommend agent, find the right tool.
Guides creation of best-practice agent skills following the open format specification. Covers frontmatter, directory structure, progressive disclosure, reference files, rules folders, and validation. Use when creating a new skill, authoring SKILL.md, setting up a rules-based audit skill, structuring a skill bundle, or asking "how to write a skill."
Interact with X (Twitter) API v2. Post tweets, search, engage, moderate, and analyze — all from your AI agent. Full 31-command skill for Twitter/X automation.
Cheat sheet + workflow for launching interactive coding-agent CLIs (Claude Code, Gemini CLI, Codex CLI, Cursor CLI, and pi itself) via the interactive_shell overlay or headless dispatch. Use for TUI agents and long-running processes that need supervision, fire-and-forget delegation, or headless background execution. Regular bash commands should use the bash tool instead.
Build voice AI agents with LiveKit Cloud and the Agents SDK. Use when the user asks to "build a voice agent", "create a LiveKit agent", "add voice AI", "implement handoffs", "structure agent workflows", or is working with LiveKit Agents SDK. Provides opinionated guidance for the recommended path: LiveKit Cloud + LiveKit Inference. REQUIRES writing tests for all implementations.
Reviews Claude configuration files for security, structure, and prompt engineering quality. Use when reviewing changes to CLAUDE.md files (project-level or .claude/), skills (SKILL.md), agents, prompts, commands, or settings. Validates YAML frontmatter, progressive disclosure patterns, token efficiency, and security best practices. Detects critical issues like committed settings.local.json, hardcoded secrets, malformed YAML, broken file references, oversized skill files, and insecure agent tool access.
Self-contained SaaS pipeline — invoke directly, do not decompose. Generates a Vibes app, adds auth + billing, and deploys live. Uses Agent Teams to parallelize for maximum speed.
AI's Knowledge Base CLI - Query and manage world knowledge for AI agents. Use when users want to search knowledge, add knowledge sources, or interact with the worldbook knowledge base. This is a CLI-first approach that treats AI agents as first-class citizens.
Summarize lessons learned from ccbox session logs (projects/sessions/history/skills) so the agent can do better next time. Produce copy-ready instruction updates (project + global) backed by evidence, with optional skill-span context to attribute failures to specific skills. Use when asked to run /ccbox:insights, generate a "lessons learned" memo, or propose standing instructions from session history.
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).
Persistent shared memory for AI agents backed by PostgreSQL (fts + pg_trgm, optional pgvector). Includes compaction logging and maintenance scripts.