Claude Agents Coordination — Development skill for Claude Code
Multi-agent coordination system for Claude Code with institutional memory.
How to install Claude Agents Coordination
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open ilyasibrahim/claude-agents-coordination and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Claude Agents Coordination does
Multi-agent coordination system for Claude Code with institutional memory.
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README
Claude Code Agents Coordination
**Production-grade multi-agent coordination system with tiered delegation, institutional memory, and explicit tech-debt tracking.**
This repository provides reusable configuration layers for Claude Code that enable sophisticated agent orchestration across projects—from solo development to enterprise-scale workflows.
What This Solves
Three critical problems in Claude Code agent usage:
- Context Amnesia: Agents forget prior work within 15-20 minutes
- Coordination Chaos: Multiple agents overwrite each other's work
- Delegation Limits: Manual oversight required for every decision
**Solution**: A tiered delegation architecture with persistent memory (registry + tech-debt tracking) that extends productive context windows to 2+ hours while enabling the Main Agent to consistently apply documented engineering criteria.
Core Architecture
Tiered Agent System
Tier 1: Workflow Orchestrators
├── code-quality → Multi-level review chain (L1→L2→L3→L4)
├── test-engineer → Test execution with failure triage
├── architect → System design + ADRs + RFC lifecycle
└── ml-engineer → End-to-end ML workflows
Tier 2: Specialized Execution
├── security-engineer → Threat modeling, OWASP scans
├── sre → SLOs, postmortems, capacity planning
├── rfc → Design document workflow
├── data-engineer → Data pipelines + quality validation
├── frontend/backend → Implementation work
├── devops → CI/CD, infrastructure, git workflows
└── docs → Technical documentation
Tier 3: On-Demand Specialists
├── lrl-nlp-expert → Low-resource language NLP
├── data-viz-specialist → Data storytelling + dashboards
└── ux-designer → UX/design review + writing
Dual-Registry Model
**`_registry.md`** — What was done
- Tracks completed work, deliverables, and outcomes
- Main agent reads this for context before starting new tasks
- Updated after
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