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

With no annotations provided, the description carries the full burden of behavioral disclosure. It meaningfully discloses that cases are audited, include revenue and pricing claims tied to public sources with evidence grades, and explicitly state what does not transfer to other builders. This goes beyond the obvious 'search' behavior and helps the agent set expectations about result quality and limitations.

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 two sentences with no filler. The first sentence front-loads the action and scope, while the second adds valuable behavioral context about evidence grades and non-transferable insights. Every sentence earns its place.

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?

There is no output schema, so the description must convey what results will contain. It does that well by stating that each case carries revenue/pricing claims, public-source links, an evidence grade, and an explicit non-transfer list. It could also mention relationship to siblings or return format, but the core information needed to invoke and interpret results is present.

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 100%, so the baseline is 3. The description does not add parameter-specific meaning beyond the schema; the schema already explains that query accepts keywords like product names, categories, or business questions, and that category is an optional exact filter.

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 uses a specific verb and resource: 'Search ProofStack's audited business-model case studies of small software products.' It clearly identifies what the tool does and hints at differentiators—audited claims, evidence grades, and non-transferable lessons—that distinguish it from siblings like get_case and pricing_benchmarks.

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 when to use the tool: when searching for case studies by keywords such as product, category, or business question. However, it does not explicitly address when not to use it or how it compares to get_case or pricing_benchmarks, leaving routing decisions to inference.

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