list_dataset_eval_runs

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

With no annotations, the description carries full behavioral disclosure responsibility. It implies a read-only listing operation but does not state side effects (none expected), auth requirements, rate limits, or default behavior like ordering or error handling. It adds minimal value beyond the tool name, only mentioning 'past eval runs with status and results'.

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 two concise sentences with zero fluff. It front-loads the purpose and mentions status and results. Every word adds value, and it is appropriately sized for a simple list operation.

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's simplicity (3 params, no output schema, no annotations), the description is mostly sufficient but lacks explicit mention of pagination or what the response structure contains beyond 'status and results'. It also does not differentiate from similar list tools, which is a completeness gap in a context with many siblings.

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 100%, so baseline is 3. The tool description does not add any additional parameter context beyond the schema's own descriptions (page, page_size, dataset_id). It does not explain how parameters interact (e.g., pagination) or when they are optional. Hence, the description adds no extra semantic value over 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 lists evaluation run results for a dataset and shows status and results. It distinguishes from sibling tools like list_evaluation_pipelines (which list pipelines, not runs) and run_evaluator (which executes, not lists). However, it could be more specific about the scope (e.g., 'all runs' vs 'filtered by date') and does not explicitly contrast with list_experiments, though the domain of eval runs is distinct.

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?

No guidance is provided on when to use this tool vs. alternatives. It does not mention when to prefer this over list_experiments, list_evaluation_pipelines, or retrieve_dataset_log. The description only states what it does, without indicating prerequisites, common use cases, or when not to use it.

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