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ZenRows
by ZenRows

batch_content

Read-only

Read a batch task's stored result by job_id and task_id; text results return inline up to max_chars, while binary results provide a presigned result_url.

Instructions

Read one Batch task's stored result, by job_id and task_id (from batch_results). A text result (HTML, Markdown, plain text, JSON) comes back inline, cut to max_chars (default 20000); a final note says when it was cut. A binary result (a PDF) is not inlined: the reply gives its result_url, presigned for 2 hours. Finding that URL reads the run's results; on a large run one call may run out of time first and answer with lookup_cursor: call batch_content again with it to go on.

BATCH_TASK_NOT_READY: the task has not finished; BATCH_TASK_FAILED: it failed (task_error holds its error); BATCH_RESULT_EXPIRED: past the job's retention (14 days by default); rerun to scrape it again.

Input Schema

NameRequiredDescriptionDefault
job_idYesBatch job id returned by batch_create or batch_list
run_idNoAn earlier run's id (from batch_status or batch_rerun). Default: the job's latest run.
task_idYestask_id from a batch_results row
max_charsNoMax characters of a text result to return (default 20000)
lookup_cursorNolookup_cursor from a previous batch_content reply on a binary result, to go on looking for its result_url

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.15.1

TDQS

A4.6/5.0
Behavior5/5

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

Adds substantial behavior beyond annotations: text results are inlined and truncated at max_chars with an explicit cut note, binary PDFs are never inlined and instead yield a 2-hour presigned result_url, large-run lookups can exhaust time and return a cursor, and the three named error codes plus the 14-day retention default are documented.

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-loads what the tool does, then failures, in two tight paragraphs with no filler, and every clause carries operational information. The prose is dense and occasionally awkwardly phrased ('Finding that URL reads the run's results'), which slightly taxes readability.

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 no output schema, the description carries the full return-value burden and does: inline text vs. result_url, truncation signaling, cursor continuation, and named error codes with their meanings. Nothing an agent needs to call or interpret the result is missing.

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?

Schema coverage is 100%, so the baseline is 3, but the description earns more: it explains max_chars' default and truncation note, the purpose of lookup_cursor as a continuation token, and that run_id defaults to the job's latest run. It contextualizes parameters rather than merely restating them.

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 ('Read') and resource ('one Batch task's stored result'), plus the exact keys (job_id, task_id) and their provenance ('from batch_results'). This cleanly separates it from batch_results, which lists rows rather than returning content.

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?

Explains the operating conditions thoroughly: when lookup_cursor appears and how to continue, and when to rerun after BATCH_RESULT_EXPIRED. It stops short of an explicit 'use this instead of batch_results when...' statement, leaving a small inference gap.

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