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Get Schema Drift Report

get_schema_drift_report
Read-only

Identify schema drift by retrieving a monitor's validation report, including check status and precise drift details with JSON path, severity, expected and actual values.

Instructions

Get what a monitor's schema validation found: per check whether it passed, and the drift items with their JSON path, severity, expected and actual value. Only returns something for monitors with schema validation on — see manage_drift_watch. Requires project context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoOnly checks at or before this UTC timestamp (ISO 8601)
fromNoOnly checks at or after this UTC timestamp (ISO 8601)
takeNoMaximum number of checks to report on, defaults to 50
monitorIdYesPublic ID (GUID) of the monitor, from list_monitors

Schema Changelog

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

  1. First observedv1.1.1

TDQS

A4.2/5.0
Behavior4/5

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

The readOnlyHint annotation already signals a safe read, and the description adds meaningful behavior beyond that: it returns per-check pass/fail plus drift item details, only returns data when schema validation is enabled, and requires project context. This is valuable context for an operation with no output schema.

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 compact and efficiently structured: the core purpose and output details come first, followed by the important precondition and context requirement. Every sentence contributes information without repetition or filler.

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?

With no output schema, the description adequately covers return contents and the key prerequisite. Minor gaps remain around exact behavior when schema validation is off (empty result vs. no report) and how to establish project context, but these are not critical for selecting and invoking the tool.

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?

Input schema documentation covers 100% of the parameters, so the schema itself already explains monitorId, from, to, and take. The description adds no parameter-specific semantics beyond the overall output context, which aligns with the baseline for high schema coverage.

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 identifies a specific verb ('Get'), a specific resource ('a monitor's schema validation'), and the exact output contents ('per check whether it passed, and the drift items with their JSON path, severity, expected and actual value'). This clearly distinguishes the tool from related siblings like get_contract_drift or list_monitor_checks.

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?

The description gives clear context for when the tool is meaningful: 'Only returns something for monitors with schema validation on'. It also points to manage_drift_watch for enabling that state. It doesn't explicitly name alternative tools to avoid, but the prerequisite and scoping are clear enough for an agent.

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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