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 goes beyond generic phrasing by stating this is a 'plain keyword scan' with 'no LLM in the loop' and that results are 'verbatim from the archive.' It also discloses return grouping by date. It omits details like case sensitivity or no-match behavior, but the key behavioral traits are covered.

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, front-loaded with the core action and scope, followed by an essential behavioral caveat about the no-LLM verbatim nature. Every sentence provides value without redundancy or excess length.

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 search tool with two well-documented parameters and no output schema, the description adequately covers the search scope, the return grouping, and the verbatim/no-LLM behavior. It lacks a few operational details (e.g., case sensitivity, handling of no matches) but is sufficient for correct tool selection and 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?

The schema already documents both parameters with 100% coverage, so the description's contribution is inherently supplementary. It adds meaningful context by specifying which fields the query searches (signal titles, details, types, metrics), which is not present in the schema. This enhances parameter understanding beyond the schema alone.

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 ('search') tied to a clear resource ('recent daily reports') and enumerates searchable fields (signal titles, details, types, metrics). This distinguishes it from sibling retrieval tools like get_report or list_reports by emphasizing keyword search and grouped-by-date results.

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 clearly implies when to use the tool: when performing a keyword or phrase search across recent report content. It does not explicitly name alternatives or state when not to use it, but the 'keyword search' framing and scope ('recent daily reports') provide strong contextual guidance.

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