verify

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

The description discloses that the tool runs the same prompt across multiple models and compares results for consistency. However, it does not reveal whether the operation is read-only, what a consistency mismatch results in, or any side effects or permission requirements. Since no annotations are provided, more detail would be beneficial.

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?

Two sentences, no waste. The first sentence states the action, the second the purpose. Ideal conciseness.

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?

The description covers the core concept but omits critical details such as the return format (what does a consistency comparison produce?), error handling, and behavior when models disagree. Without an output schema or annotations, this leaves uncertainty, but the high-level purpose is clearly communicated, so it is minimally complete.

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?

With 100% schema description coverage, the description adds only a small semantic layer by connecting 'agent' to 'multiple models' and implying the prompt is run across them. This matches the schema but doesn't introduce new parameter meaning, so the baseline of 3 is appropriate.

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 'Cross-verify' and identifies the resource (one agent's multiple models) and the action (running the same prompt and comparing). This clearly differentiates it from sibling tools like ask_all, which suggest querying rather than verification.

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 implies the tool is for verification purposes but provides no explicit guidance on when to choose it over alternatives like ask_all or ask_agent. There are no stated exclusions or scenarios, so usage is understood only from the tool's name and description.

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