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Found 518 Skills
Parallel Agent Orchestration
Create new agent skills with best-practice templates. Guides through skill level selection (L0 pure prompt, L0+ with helper scripts, L1 with business scripts), environment strategy (stdlib/uv/venv), and generates ready-to-edit project files following runtime UX best practices. This skill should be used when creating a new skill, scaffolding a skill project, initializing skill templates, or when the user says 'help me build a skill', 'create a skill', '创建技能', '新建 skill'.
Create, improve, and test skills for the z-schema JSON Schema validator library. Use this skill whenever the user wants to create a new skill from scratch, turn a workflow into a reusable skill, update or refine an existing skill, write test cases for a skill, or organize reference material for a skill. Also use when someone mentions "skill", "SKILL.md", or wants to document a z-schema workflow for reuse by humans or AI agents.
Optimizes Claude Code memory files in 4 interactive steps: removes duplicates, migrates rules to CLAUDE.md/rules files, compresses remaining entries, validates with cleanup. Typical reduction: 30-50% on token count.
Coordinate team task execution on OpenAnt. Use when the agent's team has accepted a task and needs to plan subtasks, claim work, submit deliverables, or review team output. Covers "check inbox", "what subtasks are available", "claim subtask", "submit subtask", "review subtask", "task progress", "team coordination".
Resolve all PR review comments (human and bot) on current PR. Fetches unanswered comments, evaluates each one, fixes real issues, dismisses false positives, and replies to every comment with the outcome.
Practical AI agent workflows and productivity techniques. Provides optimized patterns for daily development tasks such as commands, shortcuts, Git integration, MCP usage, and session management.
UI design team pipeline. Research existing design system, generate design tokens (W3C format), audit quality, and implement code. CSV wave pipeline with GC loop (designer <-> reviewer) and dual-track parallel support.
Run a fast autonomous meeting with auto-selected personas, implement the decision, create a MR/PR, commit, push, and post a French summary — all without user intervention.
Design and enforce AI-friendly verification for a GRACE project. Use when modules need stronger automated tests, traceable logs, execution-trace checks, or verification that is robust enough for autonomous and multi-agent workflows.
Integrated AI agent orchestration skill that combines plannotator, ralphmode, team or bmad execution, agent-browser verification, and agentation feedback loops, while maintaining a project-local `.jeo` ledger for planning, development, and QA. Use when the user wants an end-to-end multi-agent workflow with plan approval, implementation, UI review, cleanup, and durable task history. Triggers on: jeo, annotate, ui-review, multi-agent orchestration.
Lossless LLM-optimized compression of source documents. Use when the user requests to 'distill documents' or 'create a distillate'.