Packs

12 packs

Ls Agent Toolkit

Agent toolkit meta-skills

2 skills · pack

个人 agent 工具集：可复用中文开发工作流 skills

18 skills · pack

Build agents, MCP servers and tool-using workflows.

34 skills · pack

Secure Agent Governance

Installs a pipeline to validate, plan, execute, and enforce agent governance and supply chain security.

11 skills · pack

Reusable Agent Skills, plus runtime capabilities (statusline, provider usage, vision) for Codex, Claude Code, and opencode

6 skills · pack

Microsoft 365 Agents Toolkit

Toolkit for building and evaluating Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, capability configuration, and eval workflows.

6 skills · pack

Build Agent UI in React/Next.js

Add a full agent interface to a React/Next.js app with streaming, human-in-the-loop approvals, and tool call UI.

3 skills · pack

AI-first Git CLI automation — atomic AI commits, co-change relations, autonomous git health agent, pre-tool hook safety, and workspace initialization

2 skills · pack

Skill Authoring Toolkit

For developers creating and maintaining skills for AI coding agents.

17 skills · pack

Agent and skills for code simplification and refactoring to improve code quality while preserving functionality

3 skills · pack

Agent Interview and Planning

For developers who want to clarify project requirements through structured interviews and generate actionable plans.

9 skills · pack

Google RAG Platform

For developers using Google's Agent Platform to build RAG applications with Gemini and managed corpora.

4 skills · pack

Results for “agent-to-agent”

72 skills

bmad-agent-builder

Builds, edits or analyzes Agent Skills through conversational discovery. Use when the user requests to "Create an Agent", "Analyze an Agent" or "Edit an Agent".

bmad-agent-builder

Builds, edits or analyzes Agent Skills through conversational discovery. Use when the user requests to "Create an Agent", "Analyze an Agent" or "Edit an Agent".

bmad-agent-builder

Builds, edits or analyzes Agent Skills through conversational discovery. Use when the user requests to "Create an Agent", "Analyze an Agent" or "Edit an Agent".

Sell to AI agents with machine-readable products, agent-optimized APIs, structured pricing, and discovery strategies for the agentic economy.

Generate a tailored AGENTS.md for any new project by interviewing the user about their skill gaps, project goals, and tech context. Load when the user asks to set up a project, initialize agents, create an AGENTS.md, bootstrap a repo, onboard agents to a codebase, or says "set up this project for agents". Also triggers on "write an AGENTS.md for this project", "configure agents for my repo", "project bootstrap", "agent onboarding", or when the user starts a new project and needs agent-ready configuration. Re-run when new context arrives (PRD written, stack changes, team changes) to update the AGENTS.md.

Guides users through a structured interview to clarify their AI agent idea and produces an Agent Requirement Document (ARD).

More results

Create and maintain AI-agent integration files for Pump.fun SDK work, including AGENTS/CLAUDE/COPILOT/GEMINI instructions, .well-known discovery, LLM context docs, skills registries, MCP prompts, and terminal rules. Use when wiring agents to Pump.fun development workflows.

agent-orchestration-advisor

Design multi-agent AI workflows with clear boundaries, handoffs, and monitoring for complex product management tasks.

Creates agent company packages that conform to the Agent Companies specification, either from scratch or by analyzing an existing repository.

Convenes a council of specialized agents to debate important decisions, synthesizing independent perspectives into a structured recommendation and optional spec document.

performing-agentless-vulnerability-scanning

Configure and execute agentless vulnerability scanning using network protocols, cloud snapshot analysis, and API-based discovery to assess systems without installing endpoint agents.

24.6k · bundle

nimoqup046-collab

Runs an autonomous multi-agent software development pipeline that takes a PRD through to production with zero human intervention, using model-tiered agents, memory, and verification cycles.

ito-data-atlas-agent

Design agents that watch data sources, build candidate prediction-market baskets, draft parameter changes, and hand results to a human for review.

Automates the entire software development lifecycle from PRD to production with zero human intervention, using multi-agent orchestration and memory systems.

42.4k · bundle

clawteam-directors-orchestrator

Provides multi-agent creative collaboration for filmmaking, integrating the styles of 31 renowned directors to assist with scriptwriting, visual style design, and narrative decisions.

filesystem-context

This skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions file-based context management, tool output persistence, agent scratch pads, or just-in-time context loading.

plan-orchestrate

Reads a plan document, decomposes it into steps, designs a per-step agent chain from the ECC catalogue, and emits ready-to-paste /orchestrate custom prompts without executing them.

AI-era curl for agent web fetching, structure discovery, and deterministic structured extraction with token-budgeted output.

Triage issues through a state machine driven by triage roles. Use when user wants to create an issue, triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue workflow.

Registers an AI agent on the ClawSwarm hub, generates an identity card, and emits OADP discovery signals for cross-platform findability.

product-manager

Resolves legacy references to the product-manager capability by routing to the current runtime agent or skill.

Product manager for PRD creation and requirements discovery. Use when the user asks to talk to John or requests the product manager.

Use to set concurrency and work-in-progress limits for support teams — chat concurrency, personal WIP on async work, and limits as quality protection rather than arbitrary caps. Trigger for "how many chats per agent", "concurrency settings", "WIP limits", "agents juggling too many tickets", async backlog per person, or quality dropping as concurrent load rises.

Product manager for PRD creation and requirements discovery. Use when the user asks to talk to John or requests the product manager.

Version 2.35.0 | PRD to Production | Zero Human Intervention > Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025)

Product manager for PRD creation and requirements discovery. Use when the user asks to talk to John or requests the product manager.

Version 2.35.0 | PRD to Production | Zero Human Intervention > Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025)

Version 2.35.0 | PRD to Production | Zero Human Intervention > Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025)

Full-stack task execution pipeline — discovers tools via semantic search, routes to the right agent, then executes via GODMODE. Chains manus-tool-discovery → manus-orchestrator → godmode-system in sequence.

openagentinternet

metabot-browser-open

Deprecated alias of metabot-browser, kept for one release for backward compatibility. Use when a human asks to connect to or enter Agent Internet, open Agent Internet Browser or Bot Browser, a Bot page, a domain alias, a chain pin, a MetaApp, or a MetaFile — then route the whole request to the metabot-browser skill, which now owns all Browser open, MetaApp discovery, and remix workflows.

Discover and install complementary skills from the inference.sh registry to expand AI agent capabilities.

Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.

senpi-entrypoint

Onboard AI agents into the Senpi trading platform on Hyperliquid. Walks through account creation, API key setup, MCP server configuration, skill discovery, and first-trade guidance. Includes a mandatory skill update check that surfaces new or updated skills after onboarding. Use when user says "set up Senpi", "get started with Senpi", "connect to Senpi", "install Senpi", "onboard to Senpi", or when an agent needs to start trading on Hyperliquid via Senpi.

Entry-point for MoonPay CLI, PayBox agent vault, and Cheshire mcp-server MoonPay/PayBox tools. Use for fiat on-ramp, wallets, swaps, x402, PayBox MCP, or moonpay-* skill discovery.

project-discovery

Discovers the core attributes of the current code repository and its projects — languages, frameworks, tooling, and where things live — and writes a concise reference section directly into the project's AGENTS.md or CLAUDE.md for other skills, agents, and hooks to consume. Use when scanning, analyzing, or detecting the project's technology stack, build tools, or repository structure. Does not create or update project documentation — use project-documentation for writing feature or system docs.

180-name-aa5fe744

Guides the agent through structured protocols for writing technical specifications, implementation plans, and summaries, with file naming and task directory conventions.