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Found 4,915 Skills
Helps users discover and install agent skills from the open skills ecosystem (skills.sh). Use when users ask 'how do I do X', 'find a skill for X', 'is there a skill that can...', want to search for tools/templates/workflows, or express interest in extending agent capabilities.
Evaluates and optimizes agent skills using a DSPy-powered GEPA (Generate/Evaluate/Propose/Apply) loop. Loads scenario YAML files as DSPy datasets, scores outputs with pattern-matching metrics, and optimizes prompts via BootstrapFewShot or MIPROv2 teleprompters. Also generates new scenario YAML files from skill descriptions.
Compare Nim and Python scripted agent implementations and align behavior. Use when asked to port or ensure parity between Nim and Python.
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
Analyze repository structure and generate or update standardized AGENTS.md files that serve as contributor guides for AI agents. Supports both single-repo and monorepo structures. Measures LOC to determine character limits and produces structured documents covering overview, folder structure, patterns, conventions, and working agreements. Update mode refreshes only the standard sections while preserving user-defined custom sections. Use when setting up a new repository, onboarding AI agents to an existing codebase, updating an existing AGENTS.md, or when the user mentions AGENTS.md.
Wrap an existing Python agent as an Agent Stack service using agentstack-sdk server wrapper, without changing business logic.
Operate and evolve agent-memory-workbench with replay-first memory, minimal JSON edits, and a strict two-branch policy (normal + human-verification).
Dispatch code-reviewer agent for two-stage review. Use after completing implementation tasks.
Automates browser interactions using AgentGo's distributed cloud browser cluster via playwright@1.51.0. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information — running on AgentGo's remote cloud browsers instead of a local browser.
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'.