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clm_timeline_command_generate_up_timeline_excel_report

Destructive

Generate an Excel report of the UP timeline shipment list by queuing an asynchronous export request with filters for site, status, schedule dates, and sender/recipient teams, and return immediately.

Instructions

Queues an asynchronous request to build an Excel export of the shipment list view (UP timeline), filtered by site, status, schedule date range and sender/recipient teams, and returns immediately without waiting for the report to be generated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

The description adds valuable behavioral detail beyond the annotations: the operation is asynchronous, returns immediately, and does not produce the result synchronously. The annotations only indicate non-idempotent and destructive hint, so this extra context is meaningful. It does not explain how the completed report is delivered, but the async behavior is the key disclosure.

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 a single information-dense sentence that front-loads the core behavior and asynchronous nature before listing filters. Every part adds relevant information, though the sentence is somewhat long.

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

Completeness3/5

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

The description adequately captures the main behavior and primary filter dimensions, and an output schema is available to describe return values. However, with about 16 optional parameters and 0% schema description coverage, several parameters remain undocumented, leaving clear gaps for an agent that needs to configure the report precisely.

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

Parameters2/5

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

Schema description coverage is 0%, and the description only names a subset of the params: site, status, schedule date range, and sender/recipient teams. Many important parameters remain unexplained, such as FileId, Language, Ascending, OrderByField, SearchKeys, ShipmentIds, ShipmentTypes, equipment IDs, and annotation flags. With zero schema-level descriptions, the tool description should have compensated much more fully.

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: it queues an asynchronous request to build an Excel export of the shipment list view (UP timeline), and lists the relevant filters. The 'UP timeline' qualifier distinctively differentiates it from the similar sibling clm_timeline_command_generate_equipment_timeline_excel_report.

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 conveys when to use it: when an Excel export of the UP timeline is needed, and it clarifies that the call returns immediately rather than waiting for the file. It does not explicitly name alternative tools or exclusion conditions, but the resource scope and async behavior provide sufficient context.

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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