research_fanout

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

No annotations are provided, so the description carries the full burden. It describes that workers web-search, write markdown reports to files, and print digests to stdout, but lacks details on error behavior, file naming, resource limits, or batch identification. This is adequate but not comprehensive.

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 well-structured with a one-line summary, a block explaining the pipeline, and a concise Args list. Every sentence delivers value without redundancy.

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?

The description covers the main behavior and workflow integration. Given that an output schema exists, it doesn't need to explain return values. However, it could be more explicit about how to obtain the batch_id, though that is assumed to be in the output.

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 coverage is 0%, but the description provides detailed parameter semantics in the Args section, explaining the purpose of each parameter, including defaults for tier and timeout. This adds significant meaning beyond the schema.

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: 'Launch parallel grounded-research workers, one detached Antigravity (agy) job per sub-question.' It uses specific verbs and resources, and distinguishes itself from sibling tools by naming them as polling/gathering tools.

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 explicitly says it's the fan-out half of a deep-research pipeline and guides the user to poll with research_status(batch_id) and gather with collect_digests(batch_id), providing clear context on when to use this tool and alternatives.

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