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Rewrite queries into questions

rewrite_queries
Destructive

Rewrite imported raw queries ("cloud banking") into the full questions a buyer would ask an assistant, using the analysis model; the original query is kept as the prompt’s keyword. Spends a few cents per hundred queries from the balance; dryRun=true returns the rewrites without saving them. category limits it to one category. Run it after import_queries.

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": {
      "projectId": "<projectId>"
    },
    "name": "rewrite_queries"
  }
}

Input Schema

NameRequiredDescriptionDefault
dryRunNoReturn the rewrites without saving them.
categoryNoRewrite only the queries of this category.
projectIdYesThe project id, from list_projects.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The annotations already declare this as a non-read-only, destructive operation. The description adds useful context beyond that: cost is a few cents per hundred queries, dryRun avoids saving, the original query is retained as a keyword, and the analysis model is used. It still does not spell out exactly what saved data is replaced or whether changes are reversible.

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 front-loaded with the core action, then adds cost, dryRun behavior, category scope, and sequencing. Every clause carries useful information without padding.

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?

For a three-parameter mutation tool with no output schema, the description covers the main operational concerns: cost, preview mode, category scoping, and sequencing after import. It could be slightly more explicit about what is saved or overwritten when dryRun is false.

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 description coverage is 100%, so the schema already documents dryRun, category, and projectId. The description reinforces dryRun and category semantics but adds little beyond the schema and does not mention projectId.

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 a specific verb and resource: rewriting imported raw queries into full buyer-style questions. It also gives a concrete example and explicitly distinguishes the import step from the rewrite step with 'Run it after import_queries.'

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

Usage Guidelines4/5

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

It gives clear operational context: run after import_queries, use dryRun=true to preview without saving, and use category to limit scope. It does not explicitly state when not to use it or name alternatives beyond the sequencing note.

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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