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Import search queries as prompts

import_queries

Import real search queries (from a keyword tool or Search Console) as prompts, one per line, optionally as "query,intent,category". They are stored word for word, as drafts unless status=active; dryRun=true only counts what would be added. Raw keywords are not questions yet: run rewrite_queries next to turn them into buyer questions. For questions already written use add_prompts.

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>",
      "contents": "<contents>"
    },
    "name": "import_queries"
  }
}

Input Schema

NameRequiredDescriptionDefault
dryRunNoOnly count what would happen.
statusNodraft (default) or active.
contentsYesThe queries, one per line; optionally "query,intent,category".
projectIdYesThe project id, from list_projects.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations only declare the safety profile (not read-only, not destructive, closed-world); the description adds the substantive behavior: queries are stored verbatim, land as drafts unless status=active, and dryRun is a pure count. It does not cover duplicate handling, per-import limits, or whether re-importing the same lines creates duplicates, which are the remaining risks for a bulk write.

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

Conciseness4/5

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

Front-loaded with purpose and input shape, then workflow routing, then the sibling alternative. Four sentences with no filler, though the contents formatting is stated twice (once in the description, once in the schema).

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 4-parameter write tool with no output schema, the description covers purpose, input shape, write semantics, defaults, and the follow-up step. The main gap is result shape for dryRun and duplicate/limit behavior, which matters because no output schema exists to explain the response.

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 contents formatting, the status enum and default, and dryRun are already documented in the schema. The description largely restates them, adding only the 'stored word for word' nuance, so the baseline of 3 applies.

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?

States a specific verb (import) and resource (real search queries) plus the destination (as prompts) and the accepted input format. It also distinguishes itself from the two closest siblings by name, so an agent can tell it apart from add_prompts and rewrite_queries without opening any schema.

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?

Explicit routing: raw keywords belong here and need rewrite_queries afterwards, whereas already-written questions belong in add_prompts. It also explains when to set status=active versus accepting the draft default and what dryRun is for, leaving little to inference.

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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