Easyparser — Amazon Product & Seller Data

get_bulk_item_result

Read-only

Fetch the parsed result data of a single bulk job item — the actual Amazon data that item produced (product detail, search results, seller profile, etc., depending on the job's operation). This is the same data shown in the item result modal on the Bulk Requests page of the web app.

Use this tool after get_bulk_job_items, when the user wants to see the DATA behind a specific item, not just its status. Typical flow: list_bulk_jobs → get_bulk_job_items → get_bulk_item_result.

IMPORTANT: bulk results are retained for 24 HOURS after the job completes, then they expire. If the item's data has expired, the tool returns a clear message — suggest re-running that item through the matching real-time tool (e.g. get_product_detail for a DETAIL item) to regenerate the data. This tool is free of per-call credits.

Input Schema

Name	Required	Description	Default
`item_id`	Yes	The item_id of a bulk job item — get it from get_bulk_job_items (each item row has one). This is the same ID the Data Service calls a query ID.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 11, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "description": "JSON response from the Easyparser Data Service or Account API. Non-object payloads are wrapped as { result }.",
+  "properties": {},
+  "type": "object"
+}

First observedSep 6, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds substantial non-annotation context: a hard 24-hour retention window after job completion, the expiry failure mode and its recovery path, and the fact that calls are free of per-call credits. These are exactly the operational traits an agent needs before calling.

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?

Front-loaded with the core action, then routing guidance, then the retention caveat — a sensible priority order. Slightly padded by the 'same data shown in the item result modal on the Bulk Requests page' aside, which is contextual rather than essential, but nothing is actively wasteful.

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?

With an output schema present the description need not explain return values, and it correctly focuses on the gaps structured fields cannot cover: sequencing, the 24-hour expiry, and the recovery alternative. An agent has everything required to call this correctly.

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 100% and the sole item_id parameter is already documented in the schema, including where to obtain it and its alias as a Data Service query ID. The description adds no new syntactic or format detail about item_id, so the baseline of 3 is appropriate.

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?

States a specific verb+resource: 'Fetch the parsed result data of a single bulk job item', and immediately clarifies what that data actually is (product detail, search results, seller profile). It clearly differentiates itself from get_bulk_job_items by contrasting 'the DATA behind a specific item' with 'just its status'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit precondition ('Use this tool after get_bulk_job_items, when the user wants to see the DATA...not just its status') and a full sequenced workflow: list_bulk_jobs → get_bulk_job_items → get_bulk_item_result. It also handles the negative case by telling the agent what to do when data has expired (re-run via get_product_detail).

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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