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shiiman

multi-agent-mcp

by shiiman

detect_task_type

Detects task type and persona from a task description, enabling assignment to the appropriate AI agent for parallel execution.

Instructions

タスクの説明からタスクタイプを検出する。

※ Admin のみ使用可能。

Args: task_description: タスクの説明文 caller_agent_id: 呼び出し元エージェントID(必須)

Returns: 検出結果(success, task_type, persona)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
caller_agent_idNo
task_descriptionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are present, so the description carries the full burden. It does not disclose whether the tool is read-only or has side effects, nor does it mention any error behavior. The description minimally covers the basic function but omits behavioral traits.

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 relatively short and uses bullet points for args and returns, which aids readability. However, the inclusion of Japanese and English, along with the parameter contradiction, undermines clarity. It earns a middle score for minimal structure.

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

Completeness2/5

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

Although an output schema exists, the description still explains return values, which is acceptable. However, it lacks information on error conditions, edge cases, or the significance of the returned fields. The parameter contradiction also reduces completeness.

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

Parameters1/5

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

Schema coverage is 0%, so the description must fully explain parameters. It lists both parameters but incorrectly marks 'caller_agent_id' as required while the schema shows it optional. This contradiction reduces reliability. No additional constraints or formats are provided.

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?

Description clearly states it detects task type from task description. It specifies admin-only usage, which helps distinguish from other tools. However, it does not explicitly differentiate from sibling tools that may also involve task analysis.

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?

Description indicates admin-only usage, providing a clear restriction. But it lacks guidance on when to use this tool versus alternatives, such as other detection or task inspection tools.

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

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