Agents & Orchestration

This skill should be used when designing multi-agent systems that need context isolation, supervisor or swarm coordination, explicit handoffs, parallel execution, or a decision on whether multiple agents are justified.

This skill should be used when modeling agent mental states with BDI concepts: beliefs, desires, intentions, RDF-to-belief transformations, rational agency traces, cognitive agents, BDI ontologies, and neuro-symbolic AI integration.

Use when adding A2UI rendering to any AG-UI-supported framework or custom AG-UI application, scaffolding an AG-UI app that should render A2UI, adapting an AG-UI integration to emit A2UI surfaces, or wiring the AG-UI A2UI middleware/toolkit with a compatible renderer.

This skill should be used for project-level decisions about LLM-powered systems: whether an LLM is the right primitive for the task at hand, the shape of a multi-stage batch or agent pipeline, token and cost estimation, choosing between single-agent and multi-agent at the project level, structured output design for downstream parsing, and structuring agent-assisted iteration. Use this when the unit of work is a whole project or a multi-stage pipeline. Route individual tool design to tool-design and individual skill-loading or context-budget tactics to context-optimization.

This skill should be used when the user asks to "share memory between agents", "KV cache compaction for multi-agent", "orchestrator worker context", "latent briefing", "reduce worker tokens", "cross-agent memory without summarization", or discusses Attention Matching compaction, recursive language models with workers, or token explosion in hierarchical agents.

Security auditing for code, configs, and infrastructure. Use when the user wants to audit or improve security: scan for vulnerabilities (SQL injection, XSS, command injection, path traversal), detect hardcoded secrets and credentials, review auth and authorization, check dependencies for known CVEs, audit config files for insecure defaults, or generate security reports. Trigger on "security audit", "vulnerability scan", "code review for security", "find secrets", "check for vulnerabilities", "OWASP", "CVE", or questions about code security.

This skill should be used when designing autonomous agent harnesses: research loops, evaluation scaffolds, locked and editable surfaces, durable logs, novelty gates, pruning, rollback, PR preparation, and human approval boundaries.

This skill should be used when designing hosted or background agent infrastructure: sandboxed execution, remote coding environments, warm pools, session persistence, multiplayer collaboration, self-spawning agents, or Modal-style sandboxes.

Professional finance research toolkit — backtesting (7 engines + benchmark comparison panel), factor analysis, Alpha Zoo (452 pre-built alphas across qlib158/alpha101/gtja191/academic), options pricing, 79 finance skills, 29 multi-agent swarm teams, Trade Journal analyzer, and Shadow Account (extract → backtest → render) across 18 market-data sources (tushare, yfinance, okx, akshare, baostock, tencent, mootdx, ccxt, futu, local, eastmoney, sina, stooq, yahoo, plus optional-key finnhub/alphavantage/tiingo/fmp).

Official GSAP skills for Claude, Cursor, and other AI agents — animations, timelines, ScrollTrigger, plugins, utilities, React, and performance

Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.

SOP for debugging browser automation failures on complex websites. Use when browser tools fail on specific sites like LinkedIn, Twitter/X, SPAs, or sites with Shadow DOM.

Full Stack MCP framework for python, build MCP agents, clients, and servers.

Generate production-quality SVG+PNG technical diagrams from natural language.

The team-architecture factory for Claude Code — a meta-skill that turns a domain description into an agent team and the skills they use, with six pre-defined team-architecture patterns (Pipeline, Fan-out/Fan-in, Expert Pool, Producer-Reviewer, Supervisor, Hierarchical Delegation). Claude Code용 팀 아키텍처 팩토리: 도메인 한 문장을 에이전트 팀과 스킬 세트로 변환하는 메타 스킬.

GitMCP is a tool that allows you to get the documentation for a given repository.

Unified AI router with 160+ providers, RTK+Caveman compression, auto fallback, MCP/A2A, desktop, PWA, and OpenAI-compatible APIs.

Agent Framework For Fintech

Create, analyze, proofread, and modify Office documents (.docx, .xlsx, .pptx) using the officecli CLI tool. Use when the user wants to create, inspect, check formatting, find issues, add charts, or modify Office documents.

TypeScript multi-agent framework: one runTeam() call from goal to result. Auto task decomposition and parallel execution for multi-step LLM jobs. Deploys anywhere Node.js runs.

Converts books and documents (PDF, EPUB, DOCX, HTML, Markdown, plain text, RTF, MOBI/AZW with Calibre) into structured agent skills, extracting frameworks, mental models, principles, techniques, and anti-patterns. Use when the user wants to study a document through GitHub Copilot CLI, Amp, or Claude Code, apply an author's frameworks while working, or build a reusable knowledge base from a file.

MCP server that provides session-scoped tools (SubmitPlan, config_validate, etc.) to Codex via stdio transport

Feishu/Lark Integration plugin bundle

CUA Computer Use Runtime plugin bundle

CLI tool for managing Klavis AI MCP servers in Google Gemini CLI

Generate AntV Infographic syntax outputs. Use when asked to turn user content into the Infographic DSL (template selection, data structuring, theme), or to output infographic <template> plain syntax.

DeepChat app settings modification (DeepChat 设置/偏好) skill. Activate ONLY when the user explicitly asks to change DeepChat's own settings/preferences (e.g., theme, language, font size...). Do NOT activate for OS/system settings, editor settings, or other apps.

Autonomous improvement engine. 14 commands: iterate, plan, debug, fix, security, ship, scenario, predict, learn, reason, probe, improve, evals, regression.

DeepChat，一个简单易用的 Agent 客户端

Claude Code CLI commands, flags, headless mode, and automation patterns

Create handoff document for transferring work to another session

Multi-LLM orchestration — up to 8 providers check each other's work. Research, build, review, and ship with consensus gates.

Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration

Create or update continuity ledger for state preservation across clears

Real-time search engine supporting web search, vertical domain search, parallel batch search, and URL content extraction.

Workflow orchestrator that chains existing skills for feature development

Guide for integrating Agentica SDK with Claude Code CLI proxy

Build AG2 (AutoGen) multi-agent systems with slash commands: scaffold agents, wire workflows, create tools, and review code

Build AG2 (AutoGen) multi-agent systems with slash commands: scaffold agents, wire workflows, create tools, and review code

Complete collection of 28 automation hooks for event-driven workflows

Agents for academic, market, and technical research, synthesis, and reporting

Domain-specific expert agents for validation, knowledge-graph, and other specialized tasks

SDD WORK-PIPELINE Agent — Requirements analysis & development 6-agent full pipeline with DAG-based orchestration and sliding window context management

Agents for cloud infrastructure, DevOps, and database operations

Agents for code review, security audits, debugging, and quality assurance

Agents for podcasts, audio/video, transcription, OCR, and content production pipelines

Onboard AI agents like fresh engineers: generate, inject, and maintain a compressed AIBOARDING.md per repo via committed hooks

Agents for data engineering, machine learning, and AI development