Skip to main content
Glama
shiiman

multi-agent-mcp

by shiiman

create_agent

Create a new agent to assign a role and working directory for parallel AI CLI task execution in tmux sessions.

Instructions

新しいエージェントを作成する。

単一セッション方式: 左右40:60分離レイアウト

  • Owner: tmux ペインに配置しない(実行AIエージェントが担う)

  • 左 40%: Admin (pane 0)

  • 右 60%: Worker 1-6 (pane 1-6)

  • Worker 7以降は追加ウィンドウ(2×5=10ペイン/ウィンドウ)

※ Owner と Admin のみ使用可能。

Args: role: エージェントの役割(owner/admin/worker) working_dir: 作業ディレクトリのパス ai_cli: 使用するAI CLI(claude/codex/agy/cursor、省略でデフォルト) caller_agent_id: 呼び出し元エージェントID(必須)

Returns: 作成結果(success, agent, message または error)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roleYes
ai_cliNo
working_dirYes
caller_agent_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description bears the full burden. It discloses the layout behavior and role restrictions, but does not detail side effects, idempotency, or error conditions. For a creation tool, this is adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and includes an Args section, but the layout details (40:60 split, pane numbers) are verbose and may not be necessary for tool invocation. It could be more concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description covers purpose, parameters, and return values. However, it lacks context on prerequisites (e.g., whether a workspace must exist) and potential errors. It is adequate but not comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must add meaning. It provides descriptions for all parameters and indicates allowed values for 'role' and 'ai_cli'. However, it contradicts the schema by marking 'caller_agent_id' as required ('必須') while the schema lists it as optional. This inconsistency reduces reliability.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states '新しいエージェントを作成する' (create a new agent) and provides specific layout details, making the purpose clear. However, it does not explicitly distinguish from sibling tools like 'initialize_agent', though the layout details imply a specific type of agent creation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for creating a new agent with specific roles, and notes 'Owner と Admin のみ使用可能' (only Owner and Admin can use). However, it does not provide guidance on when not to use or mention alternatives like 'initialize_agent'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/shiiman/multi-agent-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server