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graph-batch

Destructive

Combine multiple Graph requests into one batch call to parallelize reads, sequence dependent writes, or batch Excel updates, reducing round-trips and latency.

Instructions

Combine up to 20 Graph requests into a single HTTP call. Body: { requests: [{ id: '1', method: 'GET'|'POST'|'PATCH'|'DELETE', url: '/me/messages?$top=5', headers?: {...}, body?: {...}, dependsOn?: ['1'] }, ...] }. Returns { responses: [{ id, status, body, headers }] } in arbitrary order — match by id. Use cases: (1) parallelize many small reads (e.g. fetch 15 mail messages by id in one round-trip); (2) sequence dependent writes via dependsOn; (3) batch many Excel range writes into one call to dramatically reduce latency on large workbook builds. Note: each sub-request URL is relative to the Graph version root (/me/..., /drives/..., NOT https://graph.microsoft.com/v1.0/...).

💡 TIP: Combine up to 20 Graph requests into a single HTTP call. Body: { requests: [{ id: '1', method: 'GET'|'POST'|'PATCH'|'DELETE', url: '/me/messages?$top=5', headers?: {...}, body?: {...}, dependsOn?: ['1'] }, ...] }. Returns { responses: [{ id, status, body, headers }] } in arbitrary order — match by id. Use cases: (1) parallelize many small reads (e.g. fetch 15 mail messages by id in one round-trip); (2) sequence dependent writes via dependsOn; (3) batch many Excel range writes into one call to dramatically reduce latency on large workbook builds. Note: each sub-request URL is relative to the Graph version root (/me/..., /drives/..., NOT https://graph.microsoft.com/v1.0/...).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
includeHeadersNoInclude response headers (including ETag) in the response metadata
excludeResponseNoExclude the full response body and only return success or failure indication
Behavior5/5

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

Beyond the annotations (destructiveHint=true, readOnlyHint=false), the description adds crucial behavioral details: responses are in arbitrary order (match by id), sub-request URLs must be relative to the Graph version root, and the tool supports both parallel and dependent execution via dependsOn. This fully informs the agent of the tool's behavior.

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 lengthy but well-structured, with a clear introduction of purpose, followed by body format, return format, use cases, and a note. Every sentence adds value, though some repetition (e.g., the tip mirrors earlier content) could be eliminated. It is front-loaded with key information.

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?

Given the tool's complexity (nested body, no output schema) and the provided annotations, the description covers the essential aspects: request format, return format, relative URL requirement, and use cases. It does not mention error handling or partial failure behavior, but it is sufficiently complete for an agent to use the tool 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?

The input schema provides descriptions for includeHeaders and excludeResponse, but the critical 'body' parameter lacks schema description. The description compensates by detailing the body structure (requests array with id, method, url, headers?, body?, dependsOn?), adding significant meaning beyond the schema. This covers the gap well.

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's purpose: 'Combine up to 20 Graph requests into a single HTTP call.' This specific verb+resource formulation differentiates it from sibling tools that handle individual Graph operations, making its role as a batching utility unmistakable.

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 explicitly lists three use cases (parallel reads, dependent writes, Excel range writes) which guide when to use the tool. While it does not explicitly state when not to use it, the use cases imply it is for multiple requests, providing sufficient context for selection.

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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