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Glama

get_recent_changes

Filter Microsoft Graph API change history by date, endpoint, object type or name, change kind, and source to track schema changes and updates.

Instructions

Structured, filterable query over the change history — filter by date, endpoint, object type/name, change kind, and source.

Input Schema

NameRequiredDescriptionDefault
limitNo
sinceNoISO date (YYYY-MM-DD); defaults to 7 days ago
sourceNo
endpointNo
change_kindNo
object_nameNoe.g. group, user, conditionalAccessPolicy
object_typeNoe.g. EntityType, EnumType, ComplexType, ObjectInstance

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.10.23
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full disclosure burden, yet it says nothing about result ordering, pagination/limit behavior, the size or shape of the response, or read-only safety. 'Structured' hints at machine-readable output but no behavioral traits are actually disclosed.

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?

A single front-loaded sentence with the filterable dimensions listed compactly after a dash; zero filler. It is lean to the point that needed behavioral context is absent, but as prose it is well structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Seven optional parameters, no annotations, no output schema, and only 43% schema description coverage — this definition needed to explain the default 7-day window, the limit cap of 200, and result ordering. None of that is present, so an agent cannot predict what it will get back.

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?

The description enumerates the filter dimensions (date, endpoint, object type/name, change kind, source), which maps to 6 of the 7 parameters, but adds no semantics beyond the schema — the enums and the 'since' default are already documented. It omits 'limit' entirely and gives no hints on result-window behavior.

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+resource ('structured, filterable query over the change history') and enumerates the filter dimensions, so the operation is immediately clear. It never distinguishes itself from siblings like search_changes, get_object_history, or get_node_timeline, which also read change/history data.

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 word 'structured, filterable' implies this is the path for narrowing a history query by known fields, but there is no explicit when-to-use, when-not, or named alternative (e.g., versus search_changes for free-text lookups). Usage is inferable only from the purpose statement.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.