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

With no annotations, the description carries the behavioral burden and does add useful context: data is aggregated 'across all learners' and includes error frequencies, candidate counts, and mastery recovery rates. However, it does not state read-only status explicitly, nor mention freshness, permissions, or whether results are globally aggregated versus per-cohort.

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 definition is a single front-loaded sentence with no redundant phrasing. Every clause describes a concrete part of the resource or return data.

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 two-parameter read tool with no output schema, the description sufficiently explains what is returned (segmented mistakes plus frequencies, candidate counts, and mastery recovery rates). It does not need to explain return structure because no output schema exists, but it could say more about usage context.

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 coverage is 100%, so both parameters are already documented. The description adds human-readable section labels ('Rules of the Road, Road Signs, Vehicle Controls') beyond the enum values, but does not elaborate on the limit parameter or its default/max behavior.

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 ('Retrieve') and resource ('most failed K53 test questions'), with clear scope ('South Africa', 'across all learners') and segmentation. It is clear enough to distinguish from a generic search, though it does not explicitly differentiate itself from siblings like get_outcomes_summary or search_k53.

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 explains what the tool returns but gives no explicit guidance on when to use it instead of alternatives, nor any prerequisites or exclusions. An agent must infer its use case from the name and purpose alone.

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