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By EricGrill
Deploy and orchestrate PicoClaw agent fleets on remote Linux hosts via SSH for parallel execution of fast, ephemeral one-shot tasks across multiple machines.
npx claudepluginhub ericgrill/agents-skills-plugins --plugin anthropic-rust-analyzer-lspShare bugs, ideas, or general feedback.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Multi-agent orchestrator for Claude Code. Track work with convoys, sling to polecats. The Cognition Engine for AI-powered software factories.
Complete collection of 117 specialized AI agents across 11 categories
High-intelligence Claude Code copilot with deep code reasoning, evidence-driven planning, orchestration-first execution, model routing, context budgeting, CI/CD integration, enterprise security, plugin development, prompt engineering, performance profiling, agent teams, channels (event-driven autonomy with CI webhook, mobile approval relay, Discord bridge, and fakechat dev profile), interactive tutorials, LSP integration, security-hardened hook script library, MCP Prompts coverage, common workflow packs, runtime selection guide, computer-use patterns, checkpointing, scheduled-task blueprints, repo bootstrap scanner, hook policy engine (8 installable packs), layered memory deployment, role-based subagent packs (implementer, debugger, migration-lead, dependency-auditor, release-coordinator), 5 agent-team topology kits, autonomy operating mode (4 profiles + 3 gates), and a queryable 15-tool MCP documentation server with autonomy advisor.
Context management and multi-agent orchestration with performance optimization tools
Use this agent when monitoring system health, optimizing performance, managing scaling, or ensuring infrastructure reliability. This agent excels at keeping studio applications running smoothly while preparing for growth and preventing disasters. Examples:\n\n<example>\nContext: App experiencing slow performance
Ultra-compressed communication mode. Cuts ~75% of tokens while keeping full technical accuracy by speaking like a caveman.
Automated code review for pull requests using multiple specialized agents with confidence-based scoring
Context management with save and restore capabilities
Customer support and sales automation agents
Team collaboration with DX optimization, issue tracking, and standup notes
LLM application development with RAG, embeddings, LangChain, and prompt engineering
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