Orchestrate multi-agent AI workflows by delegating tasks to specialist sub-agents using a scientific delegation framework. Structure prompts with WHERE (context), WHAT (task), WHY (criteria) to guide specialists while preserving their autonomy in HOW (implementation). Enables coordinated task planning, sub-agent prompting, and specialist coordination in Claude environments.
Scientific delegation framework for orchestrators coordinating sub-agents. Provides WHERE-WHAT-WHY context patterns while preserving agent autonomy. Use when delegating tasks, structuring sub-agent prompts, planning multi-agent workflows, or coordinating specialist agents.
Scientific delegation framework for orchestrators — provide observations and success criteria while preserving agent autonomy. Use when assigning work to sub-agents, before invoking the Agent tool, or when preparing delegation prompts for specialist agents.
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npx claudepluginhub jamie-bitflight/claude_skills --plugin agent-orchestrationRead The Fucking Prompt — finds the strongest user reaction to an AI instruction-following failure in a chosen session, reconstructs the triggering assistant output, and renders a shareable terminal-style PNG.
This skill should be used when the model needs to ensure code quality through comprehensive linting and formatting. It provides automatic linting workflows for orchestrators (format → lint → resolve via concurrent agents) and sub-agents (lint touched files before task completion). Prevents claiming "production ready" code without verification. Includes linting rules knowledge base for ruff, mypy, and bandit, plus the linting-root-cause-resolver agent for systematic issue resolution.
When setting up commit message validation for a project. When project has commitlint.config.js or .commitlintrc files. When configuring CI/CD to enforce commit format. When extracting commit rules for LLM prompt generation. When debugging commit message rejection errors.
Comprehensive Perl 5.30+ development plugin with modular skills for scripting, CPAN ecosystem, environment setup, testing, linting, and validation. Includes specialized agents for script development, code auditing, and CLI architecture.
Build FastMCP 3.x Python MCP servers — covers provider/transform architecture (including CodeMode, Tool Search, and server-level transforms), component versioning, session state, authorization (MultiAuth, PropelAuth, connection-pooled token verifiers), evaluation creation, Pydantic validation, async patterns, STDIO and HTTP transports, nginx reverse proxy deployment, background tasks, Prefab Apps UI, security patterns, client SDK usage, testing, deployment, and migration from FastMCP v2. TypeScript is a legacy reference only and is not updated for v3.
Multi-agent orchestration with AI SDK v5 - handoffs, routing, and coordination for any AI provider (OpenAI, Anthropic, Google)
Multi-agent orchestrator — supervisor loop that launches agents to implement plans
Sub-agent runner — runs agent definitions on Codex, Claude Code, Cursor CLI, or Gemini CLI from any host AI tool.
Multi-agent collaboration plugin for Claude Code. Spawn N parallel subagents that compete on code optimization, content drafts, research approaches, or any problem that benefits from diverse solutions. Evaluate by metric or LLM judge, merge the winner. 7 slash commands, agent templates, git DAG orchestration, message board coordination.
HelloAGENTS — The orchestration kernel that makes any AI CLI smarter. Adds intelligent routing, unified QA gates, safety guards, and notifications.
Multi-agent orchestrator for Claude Code. Use when user mentions gastown, gas town, gt commands, convoys, polecats, rigs, slinging work, multi-agent coordination.