get_evidence

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

With no annotations, the description carries the behavioral burden. It usefully discloses that the result is document passages, that they correspond to GROUNDS edges, and that they are ordered strongest first, but it does not cover permissions, error behavior, or what happens when no evidence exists.

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 front-loaded sentence with no wasted words. It puts the purpose and ordering behavior immediately in view.

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?

For a simple one-parameter read tool with no output schema and no annotations, the description covers the essential purpose and ordering but leaves the return shape and failure/empty cases unspecified.

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 coverage is 0% and the sole parameter belief_id is undocumented in the schema. The description contextualizes belief_id as the belief whose grounding evidence is returned, which is helpful, but it does not specify ID format or additional semantics.

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 uses a specific verb ('Return') and resource ('document passages grounding a belief'), and clarifies the underlying relation ('GROUNDS edges'). It distinguishes itself from belief-detail tools like get_belief, though it does not explicitly name a sibling alternative.

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?

It implies the tool is used when evidence for a belief is needed, but it gives no explicit when-to-use guidance, no when-not-to-use guidance, and does not mention alternatives such as get_belief or query_relevant.

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