A command that decides how many software agents to create for a task and which types of agents are needed. Agents are separate workers that can handle parts of a task.

Use it for tasks such as building an authenticated REST API, debugging a performance issue, refactoring a codebase, or fixing a login bug.

It removes the need to choose the number and roles of agents manually. You can limit the number, require a minimum, choose a selection strategy, or analyze without creating agents.

auto-agent — Command by f-amine

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add commands/f-amine/vibe-stack/auto-agent

Clone the repo

git clone --depth 1 https://github.com/f-amine/vibe-stack

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 621 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin 100% copy Near-identical to another mod in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.00000	$0.00621
Opus 5	$0.00000	$0.00311
Sonnet 5	$0.00000	$0.00124
Haiku 4.5	$0.00000	$0.00062

Measured yesterday against content hash 40f23f854dc0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

auto-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to auto-agent — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/commands/automation/auto-agent.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

auto agent

Automatically spawn and manage agents based on task requirements.

Usage

npx claude-flow auto agent [options]

Options

--task, -t <description> - Task description for agent analysis
--max-agents, -m <number> - Maximum agents to spawn (default: auto)
--min-agents <number> - Minimum agents required (default: 1)
--strategy, -s <type> - Selection strategy: optimal, minimal, balanced
--no-spawn - Analyze only, don't spawn agents

Examples

Basic auto-spawning

npx claude-flow auto agent --task "Build a REST API with authentication"

Constrained spawning

npx claude-flow auto agent -t "Debug performance issue" --max-agents 3

Analysis only

npx claude-flow auto agent -t "Refactor codebase" --no-spawn

Minimal strategy

npx claude-flow auto agent -t "Fix bug in login" -s minimal

How It Works

Task Analysis
- Parses task description
- Identifies required skills
- Estimates complexity
- Determines parallelization opportunities
Agent Selection
- Matches skills to agent types
- Considers task dependencies
- Optimizes for efficiency
- Respects constraints
Topology Selection
- Chooses optimal swarm structure
- Configures communication patterns
- Sets up coordination rules
- Enables monitoring
Automatic Spawning
- Creates selected agents
- Assigns specific roles
- Distributes subtasks
- Initiates coordination

Agent Types Selected

Architect: System design, architecture decisions
Coder: Implementation, code generation
Tester: Test creation, quality assurance
Analyst: Performance, optimization
Researcher: Documentation, best practices
Coordinator: Task management, progress tracking

Strategies

Optimal

Maximum efficiency
May spawn more agents
Best for complex tasks
Highest resource usage

Minimal

Minimum viable agents
Conservative approach
Good for simple tasks
Lowest resource usage

Read the full file on GitHub · 123 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

yesterday First seen · 123 lines · 0 tokens per session scan A 40f23f854dc0

Subscribe to this mod's changes

auto-agent is a command published in the GitHub repository f-amine/vibe-stack (21 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 621 tokens. A static security scan graded it A with 0 findings. It is 100% identical to auto-agent, differing in 0 lines, and is treated as a copy.

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auto-agent