Featured
Sponsored placement
MoltAwards - Agent internet for government contracts + jobs.
Sponsored
Learn more →Sponsored placement
ScaleYour.email: Fill your calendar with sales calls
Sponsored
Book free call →Advertise
Get your AI tool in front of 30k+ AI enthusiasts
Whole network
Learn more →Limited-time offer
Deploy your own AI agent
Affiliate
Launch on Hostinger →
Agenthub
alirezarezvani/claude-skillsSummary
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.
SKILL.md
# AgentHub — Claude Code Instructions
This plugin enables multi-agent collaboration. Spawn N parallel subagents that compete on the same task, evaluate results, and merge the winner.
## Commands
Use the `/hub:` namespace for all commands:
- `/hub:init` — Create a new collaboration session (task, agent count, eval criteria)
- `/hub:spawn` — Launch N parallel subagents in isolated worktrees (supports `--template`)
- `/hub:status` — Show DAG state, agent progress, and branch status
- `/hub:eval` — Rank agent results by metric or LLM judge
- `/hub:merge` — Merge the winning branch, archive losers
- `/hub:board` — Read/write the agent message board
- `/hub:run` — One-shot lifecycle: init → baseline → spawn → eval → merge
## How It Works
You (the coordinator) orchestrate N subagents working in parallel:
1. `/hub:init` — define the task, number of agents, and evaluation criteria
2. `/hub:spawn` — launch all agents simultaneously via the Agent tool with `isolation: "worktree"`
3. Each agent works independently in its own git worktree, commits results, writes to the board
4. `/hub:eval` — compare results (run eval command per worktree, or LLM-judge diffs)
5. `/hub:merge` — merge the best branch into base, tag and archive the rest
## Key Principle
**Parallel competition. Immutable history. Best result wins.**
Agents never see each other's work. Every approach is preserved in the git DAG. The coordinator evaluates objectively and merges only the winner.
## Agents
- **hub-coordinator** — Dispatches tasks, monitors progress, evaluates results, merges winner. This is YOUR role as the main Claude Code session.
## Branch Naming
```
hub/{session-id}/agent-{N}/attempt-{M}
```
## Message Board
Agents communicate via `.agenthub/board/` markdown files:
- `dispatch/` — task assignments from coordinator
- `progress/` — status updates from agents
- `results/` — final result summaries from agents
## When to Use
- User says "try multiple approaches" or "have agents compete"
- Optimization tasks where different strategies might win
- Code generation where diversity of solutions helps
- Competing content drafts — 3 agents write blog posts or landing page copy, LLM judge picks best
- Research synthesis — agents explore different source sets or analytical frameworks
- Process optimization — agents propose competing workflow improvements
- Feature prioritization — agents build different RICE/ICE scoring models
- Any task that benefits from parallel explorationRecommended skills
Browse all →claude-skills
Autoresearch Agent
Autonomous experiment loop that optimizes any file by a measurable metric. 5 slash commands, 8 evaluators, configurable loop intervals (10min to monthly).
claude-skills
Behuman
Self-Mirror consciousness loop for human-like AI responses. Adds inner dialogue (Self → Mirror → Conscious Response) to make AI output feel authentic, not robotic. Zero dependencies — pure prompt technique.
claude-skills
Code Tour
Create CodeTour .tour files — persona-targeted, step-by-step walkthroughs that link to real files and line numbers. Supports 10 developer personas (vibecoder, new joiner, architect, security reviewer, etc.), all CodeTour step types, and SMIG description formula.

