research_rank_results

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds the behavioral detail that missing values are handled 'explicitly', which is useful context, but it never says how (skipped, ranked last, error), leaving the actual behavior ambiguous.

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?

A single, front-loaded sentence with zero filler. The verb 'rank' leads and the scoping details follow, so an agent can parse intent immediately.

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, so the description should convey what the tool returns (ordered rows, rank positions) and how limit/direction affect output, but it does none of this. For a 4-parameter tool with a 0% covered schema, the description is too thin to fully guide correct invocation.

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 description coverage is 0% and the metric property has an empty description, so the description must compensate. It clarifies that metric is a finite numeric field and that rows are backtest rows, but it says nothing about what limit means (top-N truncation) or the effect of direction, leaving half the parameters unexplained.

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 (rank) and resource (supplied backtest result rows) scoped to a finite numeric field, with a note on missing-value handling. This is concrete enough to distinguish it from the sibling research_* metrics/statistics tools, though it doesn't explicitly name an alternative.

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 phrase 'supplied backtest result rows' implies the context in which to use it (when you already have rows to order), but there is no explicit when-to-use, when-not-to-use, or reference to alternatives like research_equity_metrics or research_trade_statistics. Guidance is inferred rather than stated.

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