batch_create

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

With no annotations provided, the description carries full burden and delivers substantial behavioral context: it discloses cost implications (50% cheaper), turnaround time (~24 hours), workflow dependencies, file size constraints, and what the tool returns (batch job ID and initial status). It doesn't mention error handling, rate limits, or authentication requirements, but provides more behavioral detail than most descriptions without annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with clear sections (COST, TURNAROUND, WORKFLOW, SUPPORTS, Returns) using concise bullet-like formatting. Every sentence adds value: cost/timing benefits, workflow steps, constraints, and return values. No wasted words while maintaining excellent readability.

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

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

For a complex batch creation tool with 6 parameters, nested objects, and no output schema, the description provides exceptional completeness. It covers purpose, workflow integration, cost/timing, constraints, usage patterns, and return values. Given the absence of annotations and output schema, it successfully compensates by providing the contextual information an agent needs to use this tool effectively within the broader batch processing ecosystem.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 parameters thoroughly. The description adds some semantic context by explaining the two primary usage patterns (inline requests <20MB vs. file-based JSONL for large batches) and referencing the workflow, but doesn't provide additional parameter meaning beyond what's in the schema descriptions. This meets the baseline expectation when schema coverage is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('CREATE BATCH JOB'), resource ('async content generation batch job with Gemini'), and distinguishes it from siblings by focusing on content generation (vs. embeddings, processing, or other batch operations). It explicitly mentions the workflow and cost/turnaround characteristics that differentiate it from standard API calls.

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

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

The description provides explicit guidance on when to use this tool (for async content generation with cost/turnaround benefits), when to use alternatives (inline vs. file-based approaches), and references sibling tools for the complete workflow (batch_ingest_content, upload_file, batch_get_status, batch_download_results). It clearly outlines the multi-step process and constraints (<20MB for inline).

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