fetch_observations

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

With no annotations provided, the description must carry the burden of disclosing behavior. It only mentions two filter options and offers no details on pagination, sorting, response structure, or side effects (though 'fetch' implies read-only), leaving the agent to guess about default behavior.

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 three sentences, with the first stating the core function and the following two giving concrete filter examples. Every sentence adds value and there is no fluff, making it appropriately concise and front-loaded.

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 8 parameters and no schema descriptions or annotations, the description is incomplete. It fails to clarify pagination semantics, how filters combine, or what the output contains, and the missing explanations for six parameters create a significant knowledge gap for the agent.

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?

The input schema has 8 parameters with 0% description coverage, so the description must compensate. It explains the purpose of observation_type and trace_id, but the other six parameters (name, page, limit, project, from_timestamp, to_timestamp) are left entirely undocumented, which is inadequate.

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 identifies the tool as 'fetch observations' and enumerates the observation types (spans, generations, events), providing a specific verb and resource. It does not explicitly differentiate from the sibling tool 'fetch_observation', relying on the plural form and the filter context to imply a batch/list operation.

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 provides concrete usage guidance: using observation_type='GENERATION' for LLM calls and trace_id to retrieve observations within a trace. These are actionable directions but the description does not mention when to prefer alternatives or when this tool is not appropriate, earning a 4 rather than a 5.

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