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 does reveal the return shape (three post-mortems, each with root cause, fix, prevention rule), but it omits safety/read-only signals, no-match behavior, and meaning of the leading '$0.01' prefix. No contradiction exists.

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 compact sentence that front-loads the result count and resource type. The '$0.01.' prefix is ambiguous and may not earn its place, but the rest is efficient and focused.

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 one-parameter search tool, the description conveys the main outcome and key fields, but it leaves input semantics, edge cases, and exact output formatting to inference. With no output schema, an agent would benefit from an example or more explicit return structure.

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 has one required string parameter q with no description and 0% schema coverage. The description partially compensates by indicating that results are 'matching a symptom,' implying q represents the symptom, but it never explicitly defines q or explains expected input format.

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 names a concrete output: three real agent post-mortems matching a symptom, each with root cause, fix, and prevention rule. The tool name 'search' plus 'matching a symptom' clarifies the action, and the post-mortem focus distinguishes it from the sibling tools.

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?

There is no guidance about when to use this tool versus siblings like research, catalog, or sample. The description only implies that the user should supply a symptom, but it never states exclusions, alternatives, or required context.

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