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

The annotations already provide readOnlyHint, idempotentHint, and destructiveHint, indicating a safe read operation. The description adds the 'ecommerce' domain but does not disclose any additional behavioral traits beyond what the annotations already convey. Thus, it meets the baseline but adds minimal extra context.

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 one short, clear sentence with no extraneous words. It is front-loaded with the verb and resource, and each word adds value. No waste.

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 the tool's simplicity (one parameter, no output schema), the description covers the core functionality. It specifies the action and the identifier. The annotations provide safety context. Missing are details on return value format, but for a straightforward read-by-slug tool, this is acceptable.

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% with a single parameter 'slug' described as 'Case study slug.' The description reinforces that the slug identifies a case study and adds the 'ecommerce' qualifier, but it does not provide substantial additional meaning beyond the schema. Baseline score of 3 is appropriate.

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 'Read one ecommerce case study by slug,' specifying the verb (read), resource (ecommerce case study), and the retrieval method (by slug). It distinguishes itself from the sibling tool 'search_case_studies' which is for searching multiple studies.

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 implies usage when a specific slug is available, contrasting with the sibling 'search_case_studies' which is for querying. However, it lacks explicit guidance on when not to use this tool or mention of alternatives, relying on implicit understanding from the sibling list.

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