aiworkhub_risk_mode_precision_bench

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

The 'READ-ONLY' prefix is redundant with readOnlyHint=true, so it adds nothing. The phrase 'from adjudicated registered rows' does add real provenance context about what data feeds the metric, which is beyond the annotations. However, nothing is said about cost, freshness, or scope of the computation.

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 compact sentence with the read-only marker front-loaded. Slight waste in repeating READ-ONLY, which the annotation already declares, but there is no padding beyond that.

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?

With zero parameters and an output schema present, the description needn't explain return values, so the bar is low — but 'mode', 'language', and 'adjudicated registered rows' are never grounded, and there is no cue about when the benchmark is meaningful. For an analytics tool in a crowded metrics family, this is only minimally sufficient.

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 takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. No misleading hints about inputs are given.

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 names a specific resource — precision metrics split by mode and language, derived from adjudicated registered rows — but the verb is implicit (from the 'bench' suffix) and the domain jargon ('adjudicated registered rows') leaves the actual operation ambiguous. It does not differentiate itself from siblings like aiworkhub_quality_calibration_report or aiworkhub_runtime_coverage_preview.

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?

There is no statement of when this tool should be called, no prerequisites, and no mention of alternatives. With many quality/metrics siblings in the list, the agent is left to guess whether this or a calibration/coverage report is appropriate.

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