Create Evidence

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

Annotations indicate readOnlyHint=false, destructiveHint=false, and openWorldHint=true. The description adds that evidence is 'created' and can later be 'linked to intents,' which aligns with the mutation nature of the tool and provides helpful behavioral context (e.g., evidence is not immediately tied to an intent). No contradictions with annotations.

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 two sentences, front-loaded with the purpose and examples. Every word contributes meaning; there is no superfluous text. Ideal conciseness for an AI agent.

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 9 parameters (3 required) and full schema coverage, the description adequately explains the tool's role and how it fits into the broader workflow (evidence links to intents). It does not detail the return value, but without an output schema this is acceptable. Slightly lacking in mentioning any prerequisites or constraints beyond the schema.

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 additional meaning beyond the schema; it only gives examples of what evidence items look like. The schema sufficiently documents each parameter, so the description does not need to compensate.

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 verb ('Create') and resource ('evidence item'), and provides concrete examples such as 'discovered bug, user feedback quote, behavioral observation, or feature request.' This makes the purpose specific and easy to understand, though it does not explicitly differentiate this tool from sibling tools like 'link_evidence' or 'query_evidence'.

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 explains when to use the tool (to create evidence that can later be linked to intents) but does not provide explicit guidance on when not to use it or mention alternatives. The context of linking to intents offers some usage context, but lacks exclusion criteria or comparative advice.

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