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

Annotations already declare readOnlyHint=true, and the description does not contradict this. It adds context beyond annotations: the universe size, weekly refresh, and the components of the returned score. Since annotations cover the safety profile, the description provides supplementary but not exhaustive behavioral detail, earning a 4.

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 two sentences that front-load the core function and output, then immediately provide use-case guidance and update frequency. Every sentence adds value, with no redundancy or filler.

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 read-only tool with one optional parameter and no output schema, the description is complete: it lists return fields, explains the refresh cadence, specifies the universe scope, and gives concrete invocation triggers. The only minor ambiguity ('on the IOM') is not critical for 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?

There is only one optional parameter, and the input schema fully describes its behavior (returns historical series, tier requirement, fallback to snapshot). With schema_description_coverage at 100%, the baseline is 3, and the description adds no further parameter semantics beyond what the schema already covers.

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 returns a 0-100 durability/quality score for a curated ~217-name long-term-compounder universe, specifying the output fields (score, drivers, confidence, methodology_version) and the methodology (composite z-score with maturity-stage tilt). This distinguishes it from the many sibling tools that lack descriptive names.

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 description explicitly lists when to call: 'when the user asks about compounder quality, buy-and-hold universe health, or quality-factor durability, or when timing additions or trims to a long-horizon quality equity sleeve.' It provides clear context but does not mention when not to use or name alternatives, so it falls just short of a 5.

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