ai_evidence_validate

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

With no annotations, the description carries full burden for behavioral disclosure. It only states 'validate', implying a read-only check, but does not clarify whether the tool modifies data, requires special permissions, or has side effects. The behavioral transparency is insufficient.

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 sentence, which is concise in length but under-specified. It fails to convey essential information, making it insufficiently informative. Conciseness should not come at the cost of clarity.

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 lack of annotations, output schema, and parameter descriptions, the description is severely incomplete. It does not explain what validation entails, what results to expect, or how to use the parameter correctly. The tool definition leaves the agent with minimal guidance.

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 sole parameter 'document_json' has no description in the schema (0% coverage). The tool description adds no meaning beyond the parameter name. The agent cannot infer the expected format, constraints, or purpose of the JSON string.

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 action (validate), the resource (AI Evidence object), and the specific schema version (v0.1). This provides a specific, unambiguous purpose that distinguishes it from sibling tools like ai_evidence_inspect or ai_evidence_verify_hash.

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 is provided about when to use this tool versus alternatives. There is no mention of prerequisites, common scenarios, or exclusions. The description lacks context for decision-making.

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