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

With no annotations provided, the description carries the transparency burden. It explains the computation source (ERC-4626 share-price growth over 30 days), the protocol's self-listing rule, and the special meaning of null gaps. This goes beyond a bare name and gives the agent important interpretive context.

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 dense but every sentence earns its place: the first defines the content, the second explains the self-listing rule, and the third clarifies null semantics. It is appropriately sized for a no-parameter tool and front-loads the core meaning.

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 main return components (advertised vs realized, board summary, provenance) and the null handling. Without an output schema, it gives a solid mental model, though it does not describe the exact column layout or ordering beyond the protocol's own row being first.

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 tool has zero parameters, so the schema is trivially complete. Per the rubric, a no-parameter tool earns a baseline of 4; the description adds no parameter-specific detail because none is needed.

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 specifies exactly what is returned: the full Kerne Honesty Index, including advertised vs realized values, board summary, and provenance. It clearly distinguishes from siblings like get_row and list_rows by emphasizing the 'whole board' and additional summary/provenance content.

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?

Usage is implied rather than explicit: 'The full Kerne Honesty Index' indicates this is for retrieving the complete board, but there is no direct statement of when to use this instead of list_rows or get_row. No alternatives or exclusions are mentioned.

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