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Found 422 Skills
Targeted Chat Room: Recommend experts based on topics or accept user-specified experts to simulate multi-role conversations. Trigger methods: /定向聊天室, 「定向聊天室」
Use when starting any conversation, receiving a new task, or when uncertain which skill applies - establishes how to find and use all 64 toolkit skills, requiring Skill tool invocation before ANY response including clarifying questions
Autonomously optimize an existing AI skill by running it repeatedly against binary evals, mutating one instruction at a time, and keeping only changes that improve pass rate. Based on Karpathy-style autoresearch, but applied to SKILL.md iteration instead of ML training. Use when optimizing a skill, benchmarking prompt quality, building evals for a skill, or running self-improvement loops on reusable agent instructions. Triggers on: skill-autoresearch, optimize this skill, improve this skill, benchmark this skill, eval my skill, run autoresearch on this skill, self-improve skill.
Transform code, issues, or context into a detailed prompt/context for another LLM to fix or implement. Use when preparing comprehensive context for external LLM assistance, bug fixes, improvements, or feature implementations. Provides detailed context without implementation suggestions, letting the receiving LLM decide how to implement solutions. Focuses on "what" (problem, requirements, current state) not "how" (implementation approach).
Token-saving terse mode — no filler, no narration, just results
Use when starting a new project, adding a new agent to an existing system, or setting up workflow infrastructure from scratch.
Optimizer that refines and professionalizes AI agent skills through real usage — saves tokens, eliminates redundancy, and tightens instructions so skills cost less to run. Learns from mistakes, reviews quality, and improves over time. Observes skill execution in the current conversation, analyzes up to four sources (conversation friction, file diffs, user feedback, static diagnostic) plus accumulated lessons, and proposes concrete improvements to the target skill's SKILL.md. Works with Claude Code and compatible SKILL.md-based agent frameworks. Use after executing any skill: `/skill-optimizer [name]` or `/skill-optimizer` to auto-detect. `--review` processes accumulated lessons.
Stop LLM slop. A curated system prompt that cuts verbose, corporate-sounding LLM output by 56-71% (measured) while preserving information. Works bilingually (English + Chinese). Installs into your AGENTS.md as an always-on behavior modifier.
Generate AI video from static images using Kling 3.0, Hailuo, Luma Ray3, Runway Gen-4.5, and 8 other tools. Covers free vs paid tools, prompt writing (motion-only), camera control, and face stability. Use when user asks to animate an image, create AI video, or convert photo to video.
Use when creating specialized subagents for Claude Code plugins or the Task tool - covers description writing for auto-delegation, tool selection, prompt structure, and testing agents
Engineer system prompts for LiveKit voice agents with multilingual support. Use when creating or optimizing AI agent conversation flows.
Analyze and optimize system prompts using a structured prompting guidelines framework — AI-powered analysis and rewriting. Use when a prompt needs improvement, experiment results show quality gaps, or you want a structured review of an existing system prompt. Do NOT use when production traces show failures (use analyze-trace-failures first to identify patterns). Do NOT use to build evaluators (use build-evaluator).