List datasets for a template

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

With no annotations, the description carries the full disclosure burden, and it delivers non-obvious behavior: results are project-wide rather than restricted to the template, ordered newest first, and include id, row count and column keys. It stops short of stating pagination/result limits or whether the operation is purely read-only, so the safety and volume profile is still partially inferred.

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?

Front-loaded with what the tool is and what it returns before moving to usage and the column-key tip; every sentence carries information. It runs to three paragraphs where two would suffice, but nothing is redundant.

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?

No output schema exists, so the description must describe returns itself — it does so explicitly (id, row count, column keys) plus ordering and scope. For a single-parameter list tool, an agent has everything needed to call and interpret it.

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?

There is one parameter with 100% schema description coverage, so the schema already documents template_id and its provenance (from list_templates). The description adds domain context about what the id scopes but no format or syntax detail beyond the schema, making the baseline 3 appropriate.

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?

States a precise verb and resource ('lists the datasets a batch job can render with a given template') and pins down scope: everything in that template's project, newest first, with id, row count and column keys. That is enough to distinguish it from create_dataset, upload_dataset and list_templates without opening any schema.

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?

Gives an explicit triggering condition ('when the user refers to data they have already loaded') plus a second concrete use case (re-running a batch over an existing dataset instead of duplicating). It also names the alternatives to use when nothing fits — create_dataset or upload_dataset — so routing decisions are fully determined.

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