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Found 3,519 Skills
Interactive workflow for creating, configuring, connecting, and publishing AI agents on Agents.Hot using the agent-mesh CLI. Also covers CLI command reference, flags, skill publishing, and troubleshooting. Trigger words: create agent, manage agent, publish agent, agent description, agent setup, list agents, delete agent, connect agent, agent-mesh command, CLI help, agent-mesh flags, connect options, agent-mesh troubleshooting, TUI dashboard, publish skill, skill init, skill pack, skill version, skills list, unpublish skill, install skill, update skill, remove skill, installed skills.
Universal text artifact optimizer using GEPA's optimize_anything API for code, prompts, agent architectures, configs, and more
Commit workflow for agent-media - builds, typechecks, creates changeset, and pushes
Browser automation CLI for AI agents - create, test, and deploy web automations
Systematic documentation audit and maintenance. This skill should be used when documentation may be stale, missing, or misorganized — after feature work, refactors, dependency upgrades, or as a periodic health check. It prescribes folder structure for docs/ and manual/, dispatches haiku subagents for codebase/doc scanning, and routes doc creation to specialized agents (reference-builder, technical-writer, learning-guide) with docs-architect as quality gate.
Shell out to Cursor Agent CLI for headless IDE-aware code tasks. Supports multi-model routing (auto mode routes to Claude, Gemini, GPT). Requires Cursor Pro/Business subscription.
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 event-driven hooks for AI coding agent automation (Claude Code, Codex CLI). Configure hook events in settings or frontmatter, parse stdin JSON inputs, return decision-control JSON, and implement secure hook scripts.
Create and maintain AI coding agent subagents (.claude/agents/*.md, .codex/agents/*.md) with YAML frontmatter (name/description/tools/model/permissionMode/skills/hooks), least-privilege tool selection, delegation patterns (Task), context budgeting, and safety best practices.
Create subagent definitions (agent.md files) for independent AI workers. Use when user wants to: create an agent, build a grader/evaluator, make an A/B comparator, spawn independent workers, or create something that runs in isolation. Triggers on: '创建 agent', 'subagent', 'grade outputs independently', 'blind comparison', 'run this in parallel'. Do NOT use for skills (use trae-skill-writer) or rules (use trae-rules-writer).
Self-improving agent architecture using ChromaDB for continuous learning, self-evaluation, and improvement storage. Agents maintain separate memory collections for learned patterns, performance metrics, and self-assessments without modifying their static .md configuration.
Make application behavior visible to coding agents by exposing structured logs and telemetry. Use when asked to "add telemetry", "make logs accessible to agents", "add observability", "debug with logs", or when an agent needs to understand runtime behavior but has no way to query logs. Also use when debugging is difficult because there are no structured logs, when agent docs (CLAUDE.md, AGENTS.md) lack instructions for querying application logs, or when setting up logging infrastructure for a new or existing web application.