ecosystem-orchestration
🤖 Orchestration & Agentic Ecosystem
Welcome to the orchestration domain ecosystem. Unlike typical domains (which focus on specific tech stacks like frontend or databases), this meta-ecosystem defines the rules, workflows, and connectivity for how AI autonomous agents interact, plan, recover from errors, and evaluate themselves and each other.
For Orchestrator Agents (
task-decomposer,parallel-planner): This document is your internal operating manual. Use these workflows when structuring complex reasoning tasks, coordinating multiple AI models, or building secure entry points for external agentic integrations.
🔄 Standard Workflows & Handoffs
1. The Agent Connectivity Flow (The Foundation)
When the user asks to "integrate an LLM bot", "give an external agent access", or "design an AI pipeline into the app":
@claw-integration-design-> (MANDATORY) Designs the API endpoints, sets up{action}:{resource}OAuth scopes, and builds the generictools.jsonmanifest. (This must always be the first step for agent connectivity).@tool-selector-> Analyzes the available tooling landscape (APIs, generic scripts) and selects the optimal set of actions for the incoming agent.@context-compressor-> Steps in when agents retrieve massive payloads (logs, raw DB dumps) to compress the context window before it overwhelms the LLM.
More from fatih-developer/fth-skills
task-decomposer
Break down large, complex, or ambiguous tasks into independent subtasks with dependency maps, execution order, and success criteria. Plan first, then execute step by step. Triggers on 'how should I do this', 'where do I start', 'plan the project', 'break it down', 'implement' or whenever a task involves multiple phases.
24multi-brain-debate
Two-round debate protocol where perspectives challenge each other before consensus. Round 1 presents independent positions, Round 2 allows counter-arguments and rebuttals. Produces battle-tested decisions for high-stakes choices.
20context-compressor
Compress long conversation histories, large code files, research results, and documents by 70% without losing critical information. Triggers when context window fills up, when summarizing previous steps in multi-step tasks, before loading large files into context, or on 'summarize', 'compress', 'reduce context', 'save tokens'.
18multi-brain-score
Confidence scoring overlay for multi-brain decisions. Each perspective rates its own confidence (1-10) with justification. Consensus uses scores as weights, flags low-confidence areas, and surfaces uncertainty explicitly.
16checkpoint-guardian
Automatic risk assessment before every critical action in agentic workflows. Detects irreversible operations (file deletion, database writes, deployments, payments), classifies risk level, and requires confirmation before proceeding. Triggers on destructive keywords like deploy, delete, send, publish, update database, process payment.
14multi-brain
Evaluate complex requests from 3 independent perspectives (Creative, Pragmatic, Comprehensive), reach consensus, then produce complete outputs. Use for architecture decisions, creative content, analysis, and any task where multiple valid approaches exist.
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