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

Annotations already cover read-only, open-world, idempotent, and non-destructive behavior. The description adds useful behavioral context beyond those annotations: the data source ('consumerfinance.gov (CFPB)') and that no authentication is required. It does not contradict any annotation.

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 compact and front-loaded: purpose first, then filters, then return shape, then source/auth. Each sentence contributes useful information, though the filter list somewhat duplicates the schema and the provenance sentence is repeated in spirit by the first sentence.

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?

Given a fully documented 14-parameter schema with 100% coverage, a rich output schema, and complete safety annotations, the description provides enough high-level context—data source, auth requirement, filter capabilities, and return contents—for an agent to select and invoke the tool correctly.

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 paraphrases several filter dimensions (product, company, state, issue, date range, narrative) and mentions full-text narrative search, which helps orient the agent, but it does not add meaning beyond what the input schema already provides in detail.

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 the US Consumer Financial Protection Bureau public complaint database' and states what it returns ('complaint records with product/issue category, company, state, dates, and company response'). It clearly identifies the tool's function, though it does not explicitly differentiate it from sibling tools like cfpb-complaints.complaints.by_state or cfpb-complaints.complaints.trends.

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 gives clear context for when to use the tool: filtering by product, company, state, issue, response, timeliness, narrative presence, and date range, or full-text searching narratives. It does not explicitly mention when not to use it or route to the by_state/trends alternatives, so it stops short of full alternative guidance.

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