split_subsample

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

No annotations are provided, so the description carries full burden. It mentions the tool 'divides' and 'creates' new subsamples, implying mutation, but doesn't disclose critical behavioral traits like whether the original subsample is consumed/destroyed, what permissions are needed, or any rate limits. The description adds minimal context beyond the basic operation.

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 with three concise sentences. It's front-loaded with the core purpose, followed by usage and parameter details. Every sentence adds value, though the structure could be slightly improved by grouping related information.

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 tool has an output schema (returns information about new subsamples), the description doesn't need to detail return values. However, with no annotations, 3 parameters, and 0% schema coverage, the description is incomplete for a mutation tool—it lacks behavioral disclosures like effects on the original subsample or error conditions.

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 0%, so the description must compensate. It explains 'quantity_per_subsample' as 'If specified, each new subsample gets this amount', adding meaning beyond the schema. However, it doesn't clarify 'subsample_id' or 'num_new_subsamples' parameters, leaving two of three parameters with minimal semantic context.

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 with the verb 'divides' and resource 'subsample', specifying it creates 'multiple new subsamples'. It distinguishes from siblings like 'duplicate_sample' by focusing on splitting rather than copying. However, it doesn't explicitly differentiate from all potential siblings in the list.

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 clear context for usage: 'Create aliquots for distribution or different experiments'. This gives practical scenarios when to use the tool. However, it doesn't specify when NOT to use it or mention alternatives like 'duplicate_sample' for different purposes.

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