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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds only that filters are optional and case-insensitive for industry; it says nothing about result volume, ordering, or pagination behavior.

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?

Front-loaded with the resource and its content, followed by a compact filter list mapped one-to-one to the parameters. Efficient overall, though the phrase 'for example traffic and lead growth for named clients' is slightly loose compared to the rest.

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 read-only lookup with annotations covering safety and no output schema, the description supplies the essential context: what a case study contains and how to narrow the list. It would be stronger if it noted result ordering or roughly how many studies are returned, but nothing critical is missing for correct invocation.

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 description coverage is 0%, so the description carries the full burden and does document both parameters meaningfully: 'industry' as a case-insensitive keyword and 'service_slug' as restricting to studies that used a given service. It stops short of explaining the expected slug format or where valid slugs come from (e.g., get_services).

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 verb+resource ('TESSA's client results (case studies)') and even characterizes the content ('traffic and lead growth for named clients'), so an agent knows what it will receive. It does not explicitly distinguish itself from siblings like get_services or get_pricing, but the distinct resource (case studies) makes the separation reasonably clear.

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?

Usage is only implied: an agent infers it should call this when it wants proof/outcome examples, and the 'Optional filters' section hints at narrowing results. There is no explicit when-to-use statement, no exclusions, and no reference to alternative siblings for related content (services, pricing).

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