Loading...
Loading...
Found 480 Skills
Command-line interface for CloudAnalyzer — Agent-friendly harness for CloudAnalyzer, a QA platform for mapping, localization, and perception outputs. Supports 27 commands across 8 groups: point cloud evaluation, trajectory evaluation, ground segmentation QA, config-driven quality gates, baseline evolution, processing, visualization, and interactive REPL.
Read-only Q&A mode — answers questions about the codebase, architecture, or any topic without modifying files. Use for research and exploration before making changes.
Design thinking maestro for human-centered design processes. Use when the user asks to talk to Maya or requests the Design Thinking Maestro.
Track per-agent token usage and flag waste in parallel dispatch. Use after running parallel agents to evaluate cost vs value.
Generate project-specific design system rules for Figma-to-code workflows. Useful for capturing tokens, naming, and lint rules in one source.
When multiple tests fail, assign each failing test file to a separate subagent that fixes it independently in parallel.
Meta-skill: helps create an AGENTS.md for a new project by guiding the user through selecting the right profile from the agentic library and running the compose command. Also helps create a custom AGENTS.md from scratch when no profile fits. Invoked when the user asks to set up agent instructions, create AGENTS.md, or configure agents for a project.
A-share Market Daily Review System. Actively invoked when users mention needs such as market review, market analysis, or tomorrow's market prediction. Covers: Market Environment, Sentiment Cycle, Main Line Identification, Capital Monitoring, Post-Market Variables, Tomorrow's Combat Map. For research reference only, does not constitute securities investment consulting business or investment advice.
Use when reviewing how skills performed during a session, when the user wants to analyze skill invocations and identify improvements, or when the user says "skill retro", "review skills", "how did skills do", "improve this skill", or "skill retrospective".
Set up automated agent-driven development with Ralph. Run AI agents in a loop to implement features from user stories, verify acceptance criteria, and log progress for the next agent.
Show agent flow trace timeline and summary
Use when creating or refining SKILL.md-based skills, or diagnosing weak triggering (under/over-triggering, vague descriptions, bloated context, or missing workflow guidance).