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ask_ask_post

Read-onlyIdempotent

Ask legal questions in Korean or English. Routes to 60 specialist agents for real-time statute-verified answers.

Instructions

Ask

Main legal question endpoint — routes to 1 of 60 specialist agents with real-time statute verification.

Responses:

200: Successful Response (Success Response) Content-Type: application/json

Output Schema:

{}

422: Validation Error Content-Type: application/json

Example Response:

{
  "detail": [
    {
      "loc": [],
      "msg": "Message",
      "type": "Error Type"
    }
  ]
}

Output Schema:

{
  "properties": {
    "detail": {
      "items": {
        "properties": {
          "loc": {
            "items": {},
            "type": "array",
            "title": "Location"
          },
          "msg": {
            "type": "string",
            "title": "Message"
          },
          "type": {
            "type": "string",
            "title": "Error Type"
          }
        },
        "type": "object",
        "required": [
          "loc",
          "msg",
          "type"
        ],
        "title": "ValidationError"
      },
      "type": "array",
      "title": "Detail"
    }
  },
  "type": "object",
  "title": "HTTPValidationError"
}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesLegal question in Korean or English (max 2000 chars). Example: '부당해고를 당했는데 어떻게 해야 하나요?'
historyNoConversation history (max 6 recent turns). Each item: {role: 'user'|'model', content: '...'}
langNoResponse language: 'ko' (Korean) or 'en' (English). Auto-detected from query if omitted.
current_leaderNoCurrent leader context for handoff/deliberation.
is_first_questionNoWhether this is the user's first question in the session.
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds that it routes to specialist agents and performs real-time statute verification, which provides some behavioral context but does not disclose deeper details like authentication needs, rate limits, or potential selection logic. With strong annotations, the description adds moderate value.

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

Conciseness2/5

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

The description is cluttered with unnecessary response schema code blocks (e.g., for 200 and 422) that are not standard in MCP descriptions. The opening 'Ask' as a header feels redundant. Key information about the routing and verification is concise, but the overall structure is not efficient, with embedded JSON schemas adding noise.

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?

Given 5 parameters, nested objects, and no output schema, the description fails to explain the success response structure (the 200 output schema is empty). It does not confirm that the answer is returned in the response. The tool's behavior regarding history handling, language detection, and leader context is not elaborated. Completeness is insufficient for an agent to reliably invoke and interpret results.

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

Parameters3/5

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

Input schema has full description coverage (100%), so baseline is 3. The description does not add new information about parameters; it focuses on overall functionality. The schema itself describes the query, history, lang, current_leader, and is_first_question with examples and constraints. The description's contribution to parameter understanding is negligible.

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

Purpose5/5

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

The description states it is the 'main legal question endpoint' that routes to 1 of 60 specialist agents with real-time statute verification. This clearly identifies the tool's purpose: answering legal questions. The verb 'ask' and resource 'legal question' are specific, and the mention of 'main' helps distinguish it from sibling tools, though not explicitly.

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 this is the primary tool for legal questions but does not provide explicit guidance on when to use this tool versus siblings like ask_expert_ask_expert_post or ask_stream_ask_stream_post. No when-not or alternative recommendations are given, leaving the agent to infer usage context.

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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