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batch_process

Process content files through Gemini AI batch jobs to generate results at scale. Handles file ingestion, job creation, monitoring, and result retrieval in one automated workflow.

Instructions

COMPLETE BATCH WORKFLOW - End-to-end content generation batch processing. WORKFLOW: 1) Ingests content file (CSV, JSON, TXT, etc.), 2) Converts to JSONL, 3) Uploads to Gemini, 4) Creates batch job, 5) Polls until complete, 6) Downloads and parses results. BEST FOR: Users who want simple one-call solution. RETURNS: Final results with metadata. For more control, use individual tools (batch_ingest_content, batch_create, batch_get_status, batch_download_results).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputFileYesPath to content file (CSV, JSON, TXT, MD, JSONL)
modelNoGemini model for content generationgemini-2.5-flash
outputLocationNoOutput directory for results (defaults to current working directory)
pollIntervalSecondsNoSeconds between status checks (default: 30)
configNoOptional generation config
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the complete 6-step workflow including ingestion, conversion, upload, job creation, polling, and result download/parsing. It mentions polling behavior ('Polls until complete') and return values ('RETURNS: Final results with metadata'). However, it doesn't specify error handling, rate limits, or authentication requirements, leaving some behavioral aspects unclear.

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 appropriately sized and well-structured with clear sections (workflow steps, best for, returns, alternatives). Every sentence adds value, though it could be slightly more concise by combining some workflow steps. The information is front-loaded with the main purpose immediately stated.

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

Completeness4/5

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

For a complex 5-parameter batch processing tool with no annotations and no output schema, the description provides substantial context about the workflow, return values, and alternatives. It covers the main behavioral aspects well, though additional details about error handling or output format would make it more complete. The description compensates reasonably for the lack of structured metadata.

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%, so the schema already documents all 5 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions the workflow steps but doesn't explain how parameters like 'inputFile' or 'config' relate to those steps. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 performs 'End-to-end content generation batch processing' with a detailed 6-step workflow. It specifically distinguishes itself from sibling tools by being a 'simple one-call solution' versus the individual tools like batch_ingest_content, batch_create, etc. The verb 'processes' and resource 'batch workflow' are specific and well-defined.

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?

The description explicitly states when to use this tool ('BEST FOR: Users who want simple one-call solution') and when to use alternatives ('For more control, use individual tools...'). It names specific sibling tools (batch_ingest_content, batch_create, batch_get_status, batch_download_results) as alternatives, providing clear guidance on tool selection.

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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