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by com.newscatcherapi
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Validate Query

validate_query

Check the quality of a query before submitting a job ("Check Query Quality").

Use when:

  • You want quick feedback on whether a query is well-formed for CatchAll before spending credits on a job.

  • You want concrete suggestions to improve a vague or overly broad query.

Do not use when:

  • You want to preview auto-generated validators/enrichments (use initialize_query).

  • You want to actually run a search (use submit_query).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "validate_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesThe natural-language query to assess (required).
api_keyNoCatchAll API key. Optional if provided via x-api-key header or CATCHALL_API_KEY env var.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the tool's function and its limitations (e.g., it doesn't run searches or preview validators), which is helpful. However, it does not disclose potential side effects, API requirements, or error behavior beyond what's implied. Given no annotations, this description does a moderate job but leaves gaps such as rate limits or credit implications.

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

Conciseness5/5

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

The description is efficiently structured with a clear title, a concise summary sentence, and bullet-point usage sections. Every sentence serves a purpose, and the most critical information (what the tool does) is front-loaded. The 'Do not use when' section is particularly valuable, providing immediate exclusions. No fluff or redundancy.

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

Completeness4/5

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

Given the tool's simplicity (2 params, 100% schema coverage, output schema present), the description covers the essential purpose and usage context thoroughly. It explains what the tool is for, when to use it, and when not to, which is sufficient for an agent to decide. The existence of an output schema means the description doesn't need to explain return values. Minor gaps like potential errors or implications of the API key are not critical.

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?

Schema coverage is 100%, so the schema documents both parameters (query and api_key) with their types and descriptions. The description adds contextual meaning by implying that the query is assessed for quality, but it doesn't explain the api_key parameter beyond what the schema states. Since the schema dominates, the description adds limited value; a baseline of 3 is appropriate.

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 clearly states the tool's purpose: 'Check the quality of a query before submitting a job'. It specifies the resource (query) and the action (check/validate). Furthermore, it distinguishes itself from siblings like initialize_query and submit_query by explicitly defining what it is not for. This is a specific verb+resource construction that leaves no ambiguity.

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

Usage Guidelines5/5

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

The description provides explicit 'Use when' and 'Do not use when' sections, offering clear conditions for appropriate use and exclusions. It references sibling tools (initialize_query and submit_query) and explains when to use those alternatives instead. This is exemplary guidance for an agent to decide between 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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