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abdm_download_batch

Enqueue up to 50 URLs in one batch and track each download's status individually. Offload to AB Download Manager for faster, reliable downloads with pause/resume.

Instructions

Enqueue up to 50 URLs in a batch with per-item status tracking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNointeractive
urlsYes
queue_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsNoPer-URL results
failedYesNumber of failed submissions
submittedYesNumber of successfully submitted URLs

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.6/5.0
Behavior4/5

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

The description reveals that the operation is asynchronous enqueueing rather than immediate download, and that per-item status tracking is available—useful context not present in annotations. Annotations already signal non-read-only and non-destructive/open-world behavior, and the description is consistent with those. It doesn't detail side effects like queue creation or failure behavior, but it adds meaningful behavioral context beyond the structured hints.

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?

One sentence with no filler; the operation, cap, and status-tracking feature are all front-loaded. It earns its place by adding specifics beyond the tool name. The structure is ideal for quick agent comprehension.

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?

For a 3-parameter asynchronous batch tool, the description is too thin: it doesn't explain the mode enum, the optional queue_id, or how per-item status is surfaced or retrieved. The presence of an output schema covers return-value details, but the operational workflow (enqueue, then check status) and parameter semantics are incomplete. An agent would likely need to inspect siblings or experiment to use it confidently.

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?

With schema description coverage at 0%, the description needed to explain parameters, but only indirectly addresses 'urls' through the phrase 'URLs in a batch.' Mode and queue_id are left entirely unexplained, and even the urls format isn't expanded beyond the schema's array-of-string type. The schema's titles and enums carry the only meaning, so the description contributes almost nothing to parameter understanding.

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?

The description states a clear operation: enqueue URLs, with a concrete batch cap of 50 and per-item status tracking. This is more specific than the bare tool name and makes the tool's function unambiguous. It doesn't explicitly name sibling tools to differentiate, so it stops short of 5.

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 batch context ('up to 50 URLs', 'enqueue') gives an agent a clear sense of when to choose this over a single-download sibling like abdm_download. However, it doesn't state explicit exclusions or alternatives such as 'for a single URL, use abdm_download'. That leaves usage guidance strong but not fully explicit.

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