list_embeddings_indices

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

No annotations exist, so description carries the burden. It correctly implies a read-only operation ('list'), but does not disclose any potential side effects, authentication requirements, or performance implications. For a simple list tool, this is minimally adequate.

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?

Single sentence, no redundant information. Front-loaded with action and object.

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?

The description is too minimal. It lacks any indication of the return format (no output schema) and does not clarify how the dataset is specified. Given the tool's simplicity, some additional context about implicit context or expected output would be beneficial.

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?

Tool has no parameters (schema coverage 100% with empty schema). The description adds context that the listing is 'for a dataset', which is not captured in the schema. This is acceptable for a parameterless tool.

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?

Description clearly states the action ('list') and resource ('embeddings indices'). It distinguishes from sibling tools by being the only one listing embeddings indices. However, it ambiguously says 'for a dataset' without specifying how the dataset is determined, given no parameters.

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 provided on when to use this tool versus alternatives. The description only states what it does, without context on prerequisites, typical use cases, or when to avoid it.

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