get_skill_distribution

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

No annotations are present, so the description carries the full transparency burden. It discloses that the tool returns a report of most/least common skills and category clusters, which implies a read-only, non-mutating aggregate operation. However, it does not mention possible caveats such as data source, freshness, or how skills are derived.

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 short and front-loaded with the core purpose. It uses bullet-like structure for readability, though the 'Returns:' line is somewhat redundant with the output schema. Overall, every sentence contributes meaningfully.

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?

Given that the tool has no parameters and includes an output schema, the description is largely complete for a simple aggregate report. It defines the cohort scope and the nature of the report, though it could briefly mention how skills are defined or sourced; this is not a major gap.

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 has zero parameters, so the baseline is 4. The description adds meaning by clarifying that the output is a cohort-level distribution, but no parameter-specific explanation is required.

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 identifies the action ('get') and the resource ('distribution of skills') with a specific cohort scope ('across the student cohort'). It distinguishes itself from sibling tools like get_skill_gaps and get_skill_evidence by focusing on aggregate cohort-level distribution rather than individual skill analysis.

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 'across the student cohort' implies an aggregate, cohort-level use case, but the description does not explicitly state when to prefer this tool over sibling tools or when not to use it. There is clear context but no explicit alternatives or exclusions.

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