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

No annotations are provided, so the description carries the full burden. It states the output is 'full case study text' and that ids come from list_case_studies, which are helpful behavioral hints. However, it does not mention the language parameter's effect on the response or any other potential nuances, though the schema partially covers this. The description is not misleading but lacks depth.

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 a single concise sentence that front-loads the core function and includes the most useful usage hint. Every word earns its place; no filler or redundancy.

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 get-by-id tool with a full input schema and no output schema, the description adequately conveys the core purpose and id source. It could be slightly more complete by mentioning the language parameter's default, but that is covered in the schema. Overall, it is sufficiently complete for the tool's complexity.

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 schema covers both parameters (id and language) with descriptions, so the baseline is 3. The description adds value by explaining the provenance of the id parameter ('ids come from list_case_studies'), which helps the agent understand valid values. This extra semantic context justifies a point above baseline.

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 indicates the resource (case study) and the access method (by id), and it distinguishes itself from list_case_studies by specifying that it returns the full text. It lacks an explicit verb like 'returns' or 'retrieves', but the tool name and phrase 'Full case study text' make the purpose unambiguous.

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 states that ids come from list_case_studies, giving the agent a clear prerequisite and directing it to a sibling tool for finding valid ids. It does not explicitly state exclusions or alternatives, but the hint is valuable and sufficient for this simple read operation.

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