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query

Run one read-only Data Oil SQL SELECT statement against the database and return its rows. This host is read-only: only SELECT is accepted (SEARCH_INDEX for keyword search, vector.neighbors for meaning). Rows are capped to keep the answer inside the context; ask for a LIMIT or a narrower WHERE when the answer says more remained.

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": {
      "sql": "<sql>"
    },
    "name": "query"
  }
}

Input Schema

NameRequiredDescriptionDefault
sqlYesThe statement, with :name parameters
limitNoThe most rows to return
paramsNoValues for the :name parameters

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does a good job: it discloses the host is read-only, that only SELECT is accepted, that rows are capped to fit the context, and that the answer signals when more rows remained. It omits error behavior and expected latency, keeping it short of a 5.

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?

Three tight sentences with the read-only constraint front-loaded and no filler. The final clause about 'more remained' is slightly compressed and could be clearer, which keeps it off a 5.

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 3-parameter tool with no output schema, the description covers purpose, mutation safety, alternatives, and truncation behavior. The remaining gap is sibling differentiation — nothing tells the agent when this beats 'ask' or 'schema' — which matters for a tool with such a generic name.

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 baseline is 3. The description adds some value by explaining why a LIMIT or narrower WHERE matters (row capping and truncation signaling), but it doesn't explain the :name parameter binding beyond what the schema already says.

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?

States a specific verb and resource — run one read-only SQL SELECT against the database and return its rows — which an agent can immediately match to intent. However, it never distinguishes itself from the sibling tools 'ask' (likely natural-language querying) or 'schema' (likely schema inspection), so the agent must infer which entry point to use.

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?

It clearly states the read-only constraint ('only SELECT is accepted') and points to in-SQL alternatives (SEARCH_INDEX for keyword search, vector.neighbors for meaning). But those are SQL constructs, not sibling tools, and it gives no guidance on when to prefer 'query' over 'ask' or 'schema', which is the routing decision that matters most here.

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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