create_batch

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

Beyond the openWorldHint annotation, the description discloses key behaviors: asynchronous processing with 24h limit, cost discount, and the system prompt configuration matched from consult_gemini. No contradictions.

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 concise and front-loaded: the first sentence captures the core purpose. The bullet-style Args section is clean and avoids unnecessary prose.

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?

Given the presence of an output schema and moderate complexity (3 params, 1 required), the description covers all critical aspects: usage, constraints, related tools, and configuration. No gaps remain for this async batch submission tool.

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?

The description adds essential structure beyond the schema: it specifies that queries are a list of objects with 'custom_id' and 'prompt' strings, and notes that model 'pro' enables deep thinking. With 0% schema coverage, this compensates well, though temperature semantics could be expanded slightly.

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 tool's purpose: 'Submit a batch of queries for async processing (~50% cost discount).' This verb-resource combination immediately distinguishes it from synchronous tools like consult_gemini.

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?

Explicit guidance is provided on async nature (up to 24h), inlining context instead of tool use, and using get_batch/list_batches/get_batch_results for status. This tells the agent exactly when and how to use this tool versus alternatives.

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