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

Annotations already establish read-only/idempotent safety. Description adds valuable behavioral context: specifies the return object structure (id, type, label, notes, upload status) compensating for missing output schema, and notes 'Free' indicating no cost constraints.

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?

Four sentences, zero waste. Front-loaded with core action, followed by return format, parameter source, and cost. Every clause delivers distinct value (purpose, shape, prerequisites, pricing).

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?

For a single-parameter listing tool with no output schema, the description fully compensates by describing return values and upload status details. Prerequisites and cost are covered. Annotations handle safety profile. Nothing critical is missing.

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 100%, so baseline is 3. Description repeats the schema's explanation of model_id origin without adding additional semantic details (e.g., format constraints, validation rules) beyond what's in the structured 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?

Specific verb ('List') + specific resource ('artifacts uploaded to a custom eval model') clearly distinguishes this from siblings like atlas_list_custom_eval_models (lists models, not artifacts) and atlas_upload_custom_eval_artifact (uploads, not lists).

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?

Provides clear prerequisite guidance by specifying that model_id comes from atlas_create_custom_eval_model or atlas_list_custom_eval_models. Lacks explicit 'when not to use' or alternative comparisons, but the prerequisite chain is well-defined.

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