Browse skills

Coordinate multi-agent development pipelines using shared JSON task files. Supports Linear, DAG, and Debate modes for AI agent orchestration across code, test, docs, and monitor agents.

Persistent local memory for AI agents. Save, recall, and search project decisions as local JSON. Zero cloud, zero infrastructure — works offline.

Full website SEO audit with parallel subagent delegation. Crawls up to 500 pages, detects business type, delegates to 6 specialists, generates health score.

Provides MCP tools guidance and assistance for orchestrating AI agents and multi-step workflows.

Autonomous AI coding with spec-driven development. Implements Geoffrey Huntley's iterative bash loop methodology where agents work through specs one at a time, outputting a completion signal only when acceptance criteria are 100% met.

Provides MCP tools guidance and assistance for orchestrating AI agents and multi-step workflows.

Provides MCP tools guidance and assistance for orchestrating AI agents and multi-step workflows.

Dynamically assigns tasks to multiple agents, optimizing workflow and resource allocation for complex objectives.

Provides MCP tools guidance and assistance for orchestrating AI agents and multi-step workflows.

Provides MCP tools guidance and assistance for orchestrating AI agents and multi-step workflows.

Parcadei's agent-orchestration dynamically chains and manages multiple AI agents to achieve complex tasks efficiently.

Decompose complex tasks into specialized sub-agents for improved efficiency and nuanced problem-solving capabilities.

Provides MCP tools guidance and assistance for orchestrating AI agents and multi-step workflows.

Automatically routes tasks to optimal agents based on skills, availability, and priority within defined workflows.

Provides MCP tools guidance and assistance for orchestrating AI agents and multi-step workflows.

Agentica Claude Proxy allows you to seamlessly integrate Claude's powerful language model into your existing agents for enhanced reasoning and creative capabilities.

Eliminates unnecessary polling loops in agents, enabling faster responses and reduced resource consumption through event-driven actions.

Provides MCP tools guidance and assistance for orchestrating AI agents and multi-step workflows.

Agentic Development helps you rapidly build and refine AI agents by suggesting improvements & variations, accelerating your automation workflows.

Agentica SDK empowers developers to seamlessly integrate and control Parcadei AI agents within their applications for dynamic automation and intelligent interactions.

When the user wants to build GTM automation with code, design workflow architectures, use AI agents for GTM tasks, or implement the 'architecture over tools' principle. Also use when the user mentions

Build agents that generate rich, interactive UIs using Google's A2UI (Agent-to-User Interface) format with Google ADK (Agent Development Kit). Use when building ADK agents that need to render dynamic UI components, forms, cards, lists, or interactive elements via the A2UI declarative JSON format. Includes a Tailwind CSS + shadcn/ui design system flavor for creating beautiful, modern A2UI catalogs and components. Covers A2UI schema management, catalog configuration, A2A transport integration, response parsing/validation, custom catalog creation, and the orchestrator pattern for multi-agent UI routing.

Orchestrate complex development with AUTOMATIC parallel subagent execution, continuous dispatch scheduling, dependency analysis, file conflict detection, and IOSM quality gates. Analyzes task dependencies, builds critical path, launches parallel background workers with lock management, monitors progress, auto-spawns from discoveries. Use for multi-file features, parallel implementation streams, automated task decomposition, brownfield refactoring, or when user mentions "parallel agents", "orchestrate", "swarm", "continuous dispatch", "automatic scheduling", "PRD", "quality gates", "decompose work", "Mixed/brownfield".

Use this skill when designing, generating an MVP blueprint for, auditing, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, permissions, system prompts, planning, goals, context compaction, memory, skills, MCP/external connectors, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety.