list_dataset_logs

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 correctly implies a read-only list operation and mentions pagination/filtering, but does not disclose potential edge cases (e.g., error behavior if dataset_id is invalid, whether logs are sorted by default, or the exact response structure). It adds minimal context beyond inferred semantics.

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 a single, compact sentence that is front-loaded with the core action ('List all logs') and immediately states the key differentiators (dataset, pagination, filtering). No wasted words or redundancy.

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 simplicity of a list tool and the presence of a comprehensive schema (all parameters explicitly defined), the description is sufficient. It distinguishes from siblings by naming the dataset scope and lists the available features. The absence of an output schema is not a gap because the tool's list operation likely returns obvious data. However, there's no mention of default sort order or whether 'all logs' implies unlimited pagination, leaving minor room for improvement.

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 the parameter descriptions in the schema already provide full meaning. The description adds only a slight semantic hint that 'logs' are 'data points' and refers to 'pagination and filtering' which maps to page/page_size/filters/sort_by. This is a marginal addition, not significant enough to exceed the baseline of 3.

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 function: 'List all logs (data points) in a dataset' — a specific verb and resource. It distinguishes itself from sibling tools like list_logs (generic logs) and retrieve_dataset_log (single log) by emphasizing the dataset scope.

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 usage for listing dataset logs with pagination and filtering but does not explicitly contrast with alternatives. No when-not scenarios or references to sibling tools are mentioned, leaving the agent to infer when this tool is preferred over list_logs or retrieve_dataset_log.

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