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agenticfabriq

mnemiq

db_read

Answer natural-language questions over your database with read-only access, returning the answer, SQL, and an auditable trace. Defers when it can't answer reliably.

Instructions

Answer a natural-language question over the database (read-only). Returns the answer, the SQL run, and an auditable trace; defers honestly when it cannot answer. mode: 'instant' (cheapest, no retries), 'thinking' (default, self-repairing), or 'deep' (5 candidates + judge + agreement gate -- highest precision, ~6x cost).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo
questionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that it returns the answer, SQL, and an auditable trace, that it defers honestly when it cannot answer, and that modes affect cost and precision. This is substantial behavioral context, though it does not mention error handling or permissions, which are less critical for a read-only tool.

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?

The description is concise and front-loaded with the main purpose, then details modes. It packs a lot of useful information without fluff, though it could be slightly more structured. Every sentence earns its place.

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 read-only query tool with two parameters and no output schema, the description covers the essential behaviors: return values (answer, SQL, trace), mode options, and the honesty policy. It lacks explicit limitations like timeouts, but overall it is sufficient for an agent to call it correctly.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It does: it explains the 'mode' parameter in detail (three options with cost/behavior) and clarifies that 'question' is a natural-language query. This adds meaning beyond the bare type definitions.

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 ('answer') and resource ('database'), and explicitly marks it read-only, distinguishing it from the write tool db_write. It also implies it is not the schema tool, so an agent can tell it apart from siblings without opening schemas.

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 provides internal mode guidance (instant/thinking/deep) and cost/precision trade-offs, which helps when to choose a mode. However, it does not explicitly state when to use this tool versus alternatives like get_schema or db_write, though read-only is a clear hint. No exclusions or alternative routing are mentioned.

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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