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query

Run a read-only SQL SELECT against governed company data; policies enforce allowed access, mask sensitive values, cap rows, and log every call for audit.

Instructions

Run one read-only SELECT against the company database. Only SELECT is allowed; anything else is refused before it reaches the database. Rows come back capped by the policy (maxRows, often lower than any LIMIT you write) and protected values arrive already replaced with [MASKED_PII] or [MASKED_SECRET] — the raw values never leave the gateway, so do not plan on receiving them. A refusal is a normal outcome, not a fault. Use search instead when there is no SELECT yet and the goal is to find text. Every call is written to the audit ledger, and to a signed receipt as well when a receipt sink is configured.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYesSQL SELECT query to execute
connectorNoConnector name (optional, defaults to first allowed)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.23

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden. It discloses multiple behavioral traits: only SELECT allowed, row caps, masking of sensitive values, refusal as normal outcome, audit logging, and optional signed receipts. It also warns that raw protected values never reach the caller, which is critical for planning. This is exceptionally transparent.

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 moderately long but every sentence adds value: purpose, restriction, behavior, alternative, and audit trail. It is front-loaded and well-organized. Slightly verbose but not wasteful, so a 4 is warranted.

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?

The description covers the tool's purpose, constraints, safety features, and alternatives. Without an output schema, it doesn't specify the exact return format (e.g., column details or metadata), but it does clearly state rows come back capped and masked. Given the complexity (SQL execution with policies), it is fairly complete, though a bit more detail on response structure would be useful.

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% — both parameters have clear descriptions in the schema. The tool description adds minimal parameter-specific detail beyond what schema provides, but it does mention the connector defaults to first allowed, which is already in the schema. Given high coverage, the 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 runs a read-only SELECT query on the database, explicitly limits to SELECT, and distinguishes from sibling tools like search (used when there is no SELECT yet). It names the resource (company database) and the verb (run), making the purpose unambiguous.

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 explicitly says when to use this tool vs alternatives: 'Use search instead when there is no SELECT yet and the goal is to find text.' It also clarifies that refusals are normal, setting expectations for failed invocations. This is explicit and actionable guidance.

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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