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

Annotations already establish that this is read-only, idempotent, and non-destructive, so the description does not need to repeat those safety traits. It adds some behavioral context by explaining lens semantics and interval options, but it does not describe output format, default behaviors like trend_depth, or parameter interactions.

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 main purpose is front-loaded, and the lens and interval options are enumerated compactly. Every word contributes useful information.

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 tool with seven parameters and no output schema, the description is adequate but leaves gaps. It does not clarify how sub_lens interacts with lens, whether product filters combine with lens=product, or what the returned trend data actually looks like. Schema coverage helps, but sub_lens remains ambiguous.

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 input schema has 100% description coverage, so the baseline is 3. The description adds value beyond the schema by explaining the meaning of each lens enum value and clarifying that interval can be month, quarter, or year. This helps an agent use the most important parameters correctly, though it adds nothing for sub_lens or product filters.

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 the tool's purpose: 'Time-series trends of complaint volume.' It further specifies what each lens shows, including totals over time and breakdowns by product, company, or issue, which makes it easy to distinguish from sibling complaint tools like cfpb_search_complaints or cfpb_complaint_detail.

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 explains the available lenses and intervals, so an agent can infer when to use this tool for time-series trend analysis. However, it does not explicitly state when to prefer this tool over alternatives such as cfpb_complaint_aggregations or cfpb_state_complaints, nor does it mention any exclusions.

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