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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuine context beyond that: it discloses the returned components, notes the weekly trend is only present 'when CertArc has recorded it,' and clarifies the interpretive caveat 'A study measure, not an exam prediction' — useful framing that prevents misuse.

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 trigger condition is front-loaded in the first sentence, followed by what is returned and a closing caveat. The middle sentence is dense with enumerated components but every clause carries distinct information; only minor tightening would improve it.

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?

There is no output schema, so the description carries the burden of describing returns — and it does so thoroughly, naming each component of the readiness payload. Combined with the study-measure caveat and the default-parameter behavior in the schema, an agent has everything needed to call and interpret this tool.

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?

With 100% schema description coverage, the single `program` parameter is already fully documented including its omit-for-default behavior and the five enum values. The description doesn't restate or extend parameter meaning, which is acceptable given the schema does the work, but it adds nothing extra.

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?

States a specific resource (CertArc's Readiness Score) and enumerates its components: score parts, points within reach, points still ahead, improvement steps with links, and weekly trend. This is clearly distinguishable from siblings like get_results or get_study_summary, which deal with raw results and aggregate study data rather than readiness scoring.

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 opening sentence gives explicit trigger conditions tied to learner intents: asking about the readiness score, how it's built, how to raise it, or which sprint/exam to retake for the most points. It stops short of naming alternatives or stating when not to use it (e.g., 'for individual question results, use get_result_review'), so it doesn't reach the top of the scale.

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