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Get batch items

get_batch_items
Read-onlyIdempotent

Page through a batch's scraped results by task ID, using cursors and limits up to 50; set maxResults to auto-follow pages and return items, nextCursor, hasMore, and stoppedBy.

Instructions

Page through a batch's results by its taskId (cursor, limit up to 50); with maxResults the tool follows the cursors itself and answers { items, nextCursor, hasMore, stoppedBy }.

Input Schema

NameRequiredDescriptionDefault
idYes
debugNo
limitNo
cursorNo
maxResultsNoFollow cursors from cursor on and return up to this many items in all (pages of at most 50); the answer is then { items, nextCursor, hasMore, stoppedBy }.

Output Schema

NameRequiredDescriptionDefault
itemsYes
hasMoreNo
stoppedByNosize: the answer reached its size budget; read on from nextCursor.
nextCursorNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and a closed-world scope, so the safety profile is covered. The description adds real behavioral detail beyond that: that maxResults causes the tool to iterate cursors itself, and the shape of the answer ({ items, nextCursor, hasMore, stoppedBy }). That auto-pagination behavior is the key non-obvious trait.

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 dense sentence that front-loads the primary action and tucks the mode difference into a parenthetical clause. Efficient, though the trailing response-shape list makes it slightly overloaded for one sentence.

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

Completeness5/5

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

For a read-only paginated fetch with full annotation coverage and an output schema present, the description supplies what is needed: the paging model, the auto-follow option, and the result envelope. Nothing critical for correct invocation is missing, since return values are also covered by the output schema.

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?

Schema description coverage is only 20% (just maxResults), so the description must compensate, and it does add meaning for cursor, the 50-item limit, and maxResults' follow-cursors behavior. But it leaves 'id' and 'debug' unexplained, and it calls the id a 'taskId', which does not match the schema key and could mislead. Partial compensation warrants a mid score.

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 and resource: paging through a batch's results, with the identifier it keys on and the pagination modes. It is distinguishable from get_batch (metadata) and get_batch_errors (errors), though it never names those siblings explicitly to reinforce the boundary. Minor wrinkle: the text says 'by its taskId' while the required parameter is 'id'.

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 description implies usage by contrasting the two paging modes (manual cursor/limit vs maxResults auto-follow), which is genuinely helpful context. However, it gives no explicit when-to-use guidance versus siblings like get_batch, get_batch_errors, or wait_batch, so selection still requires inference.

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