scout_batch

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 mentions 'parallel' execution and includes a parameter example, but doesn't disclose critical behavioral traits such as error handling (e.g., if one query fails), rate limits, authentication needs, or what the output looks like. For a batch tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 appropriately sized and front-loaded. The first sentence states the core purpose, the second adds use cases, and the third provides a crucial parameter example. Every sentence earns its place with no wasted words, making it efficient and easy to parse.

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 that there is an output schema (context signals indicate 'Has output schema: true'), the description doesn't need to explain return values. However, for a batch tool with no annotations and 2 parameters, it should do more to cover behavioral aspects like error handling or performance implications. The description is adequate but has clear gaps in completeness for this complexity level.

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 meaningful context beyond the input schema. While schema description coverage is 100%, the description provides a concrete example of the query structure ('{"tool": "company|market|competitors|trends|product", "params": {...}}'), which clarifies the allowed tool types and param format. This enhances understanding of the 'queries' parameter, though it doesn't add much for 'max_parallel'.

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: 'Run multiple scout queries in parallel.' It specifies the verb ('run') and resource ('scout queries'), and mentions use cases ('competitive landscape analysis and bulk research'). However, it doesn't explicitly differentiate from its siblings (scout_company, scout_competitors, etc.) beyond implying this is a batch version of those individual 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 implies when to use this tool ('Perfect for competitive landscape analysis and bulk research') and suggests it's for parallel execution of multiple queries. However, it doesn't explicitly state when NOT to use it or provide clear alternatives (e.g., using individual scout tools for single queries). The context is somewhat clear but lacks explicit exclusions or named alternatives.

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