suggest_keys

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

The readOnlyHint annotation already establishes safe read behavior. The description goes beyond this by disclosing the output contents (confidence score plus reasons such as integer column, UUID format, no nulls, exact-count unique), which is valuable behavioral context for the agent.

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 concise sentence, front-loaded with the core purpose. It earns its place without unnecessary fluff, though the unexplained 'B5' is a minor distraction but does not harm overall 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?

For a simple one-parameter read-only tool, the description adequately covers the purpose and output structure. The absence of an output schema is compensated by describing what each entry contains. The 'B5' reference is a small gap but not critical.

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 schema already provides full documentation for the single 'dataset' parameter with 100% coverage. The description does not add meaningful parameter-level details beyond the schema; the cryptic '(B5)' reference does not clarify the parameter or its format.

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 tool's action ('Rank') and target ('primary-key candidates for a dataset'), which distinguishes it from sibling tools like suggest_joins or plan_query. The purpose is specific and unambiguous.

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 explicit guidance is given about when to use this tool versus alternatives. The description does not mention any exclusions, prerequisites, or comparative context with sibling tools. The intended use case is only implied by the name and purpose.

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