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

Annotations already provide readOnlyHint and idempotentHint, and the description adds behavioral detail about the return payload: 'returns the best match with a 0-1 confidence score and ranked alternatives.' This is useful context beyond the annotations, though it doesn't cover failure modes or rate limits.

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, front-loaded with purpose and example, then workflow. Every word earns its place; no redundancy or fluff.

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?

No output schema exists, but the description explains the key return elements (best match, confidence, alternatives) and the follow-up workflow. Given the tool's simplicity and 3 parameters, this is complete for an agent to select and invoke correctly.

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 100%, so the baseline is 3. The description reinforces the 'state' parameter's purpose ('Add state to disambiguate') and gives example inputs, but adds minimal new meaning beyond the schema descriptions.

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 states a specific verb ('Resolve') and resource ('messy name string to a canonical official'), with concrete examples ('Rep. Johnson', 'cornyn'). It clearly distinguishes from sibling tools by framing it as the name-to-ID resolution step, contrasting with subsequent calls to politics_official.

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?

Explicitly states when to use: 'Use this first when you have a name but not an ID; then call politics_official with best.id.' It also provides disambiguation guidance ('Add state to disambiguate'), giving clear context for use versus alternatives.

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