list_agents

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only mentions model types and a creation hint, but fails to disclose behavior such as pagination (implied by schema but not stated), rate limits, authentication needs, or return format.

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?

Three sentences with no wasted words. The purpose is front-loaded, model types are listed efficiently, and a hint is appended. Perfectly concise for the content provided.

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 no output schema and a list tool with 4 parameters, the description is incomplete. It does not describe the return structure (e.g., list of agent objects), any default ordering, or what happens with empty results. The model types hint is tangential rather than addressing completeness needs.

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 baseline is 3. The description adds no parameter-specific details beyond what the schema already provides. The mention of model types is not linked to any parameter, so no added value.

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 'List agents (AI systems to evaluate)' with a specific verb and resource. It adds context about model types, which helps clarify what agents are. However, it does not explicitly differentiate from sibling list tools like list_runs or list_test_cases.

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 a tangential hint ('Use agent_id when creating runs') but no explicit guidance on when to use this tool versus alternatives (e.g., get_agent, create_agent) or when not to use it. No usage context is given.

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