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Found 1,134 Skills
Connect to the Zhihe AI Legal Large Model Platform for legal research. This skill should be used when users need to conduct legal issue research, look up laws and regulations, retrieve similar cases, or obtain legal research reports. A Zhihe AI platform membership account is required.
Use when the user wants Luma / 拾光 / 拾光智能体 / 拾光工具 to create a complete viral-remix short-video workflow: research, rewrite, TTS, digital human, PIP materials, subtitles, BGM, and cover.
Manage Luma / 拾光 cloud assets used by generation tools, including voices, avatars, fonts, media inputs, and named groups.
Create, verify, repair, and close durable Codex goals with measurable outcomes, evidence gates, plan templates, blocker handling, completion audits, and goal-backed workflow repair.
Show agent flow trace timeline and summary
Brief description of what this skill does and when to use it. Be specific about capabilities and use cases to help agents decide when to load this skill.
USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications.
Orchestrates multiple skills to achieve high-level goals. Acts as the brain of the ecosystem to coordinate complex workflows across the SDLC.
Provides guidance on choosing between Agent Teams and Sub-agents and executing complex plans with parallel coordination. Use when implementing complex features requiring multiple specialized teammates working in parallel.
Use when you need a complete research workflow from initial literature search to polished, fact-checked document. Chains researcher -> synthesizer -> devils-advocate -> fact-checker -> editor automatically.
Google APIs made easy — Gmail, Drive, Calendar, Tasks. Unified library and gateway CLIs (go-gmail, go-drive, go-calendar, go-tasks) for AI agents. Use when user needs to work with Gmail, Google Drive, Google Calendar, or Google Tasks. Replaces gmcli, gdcli, gccli.
Choose and combine Eve storage primitives to give agents persistent memory — short-term workspace, medium-term attachments and threads, long-term org docs and filesystem. Use when designing how agents remember, retrieve, and share knowledge.