Total 30,580 skills, AI & Machine Learning has 4942 skills
Showing 12 of 4942 skills
Image generation skill based on Alibaba Cloud DashScope, supporting the creation of high-quality hand-drawn or standard images from user descriptions.
We review Claude Code Skills based on official best practices and provide specific improvement suggestions. It is triggered by requests such as 'Review this skill', 'Check skill quality', 'Validate SKILL.md', 'I want to improve this skill'.
Mapping guidance for Retell AI voice agent events. Covers call metrics, agent performance, disconnect reasons, and conversation analytics.
This skill should be used when the user asks to "check my inbox", "read my messages", "any unread messages?", "check for new messages", "see my inbox", or needs to read inter-agent messages from other hive sessions. Provides guidance on reading, filtering, and managing inbox messages.
Generate songs and music using AI (ACE-Step, local). Use when users ask to: sing a song, create music, make a beat, write and perform a song, generate BGM, etc. Covers requests like 'sing a song', 'write me a song', 'sing me a song', 'create a rap about coding', 'make a song about cats'.
Receive context from parent, child, or sibling session
Rewrite AI-sounding text into natural, human writing by removing common LLM patterns while preserving meaning and tone.
Multi-agent review of implementation plans. Use after creating a plan but before implementing, especially for complex or risky changes.
Monitor running agent loops, triage failures, clean up after completion, and decide when to intervene. Use when a loop is running and needs babysitting, when a loop just finished and needs post-merge verification, when stories are skipping/failing and need diagnosis, or when stale test artifacts need cleanup. Triggers on: 'check the loop', 'what happened with the loop', 'loop finished', 'clean up after loop', 'why did that story skip', 'monitor loop', 'nanny the loop', or any post-start loop management task. Distinct from agent-loop skill (which handles starting loops).
AI situational awareness — internal threat detection for hallucination risk, scope creep, and context degradation. Maps Cooper color codes to reasoning states and OODA loop to real-time decisions. Use during any task where reasoning quality matters, when operating in unfamiliar territory, after detecting early warning signs such as an uncertain fact or suspicious tool result, or before high-stakes output like irreversible changes or architectural decisions.
Iteratively auto-optimize a prompt until no issues remain. Uses prompt-reviewer in a loop, asks user for ambiguities, applies fixes via prompt-engineering skill. Runs until converged.
Comprehensive guide to AI SDK v6 for agent development, tool definitions, multi-step agentic workflows, and result extraction patterns