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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, but the description adds substantial context: it is free, requires no key, mandates attribution, specifies the data source (CFPB database with narrative counts through 14 Aug 2026), and notes that dispute route dates are read from the company's own site. This goes well beyond the annotations, making the tool's side effects, data freshness, and usage constraints transparent.

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 dense paragraph but well-structured: it opens with the input condition, lists the return items, and then gives source and attribution details. It front-loads the most critical info (what it returns) before the source details. While it is long, every sentence carries necessary information for such a complex tool, and there is no fluff. It earns a 4 for being appropriately detailed without being rambling.

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 fully specify what the agent can expect. It enumerates every return component: the dispute route (portal URL, phone, email, postal address, each with date read), the FCRA clock (60/30/45 days cited to statute), the CFPB complaint record narrative, and whether the company or platform can fix the error. It also notes the source and attribution requirement. An agent has everything needed to call the tool correctly and interpret the result.

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 already provides 100% coverage with descriptions for each parameter, so the baseline is 3. The description adds value by clarifying that `company` and `situation` are slugs, and it provides free index URLs for both (`https://screeningfacts.com/api/companies` and `/api/situations`). It also implicitly clarifies the meaning of the parameters by explaining what the tool returns for each. This goes beyond the schema's bare definitions.

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 states a specific verb ('return') and a precise resource: the dispute route, FCRA clock, CFPB record, and responsible party for a named screening company. It lists the fourteen companies and clearly differentiates from sibling tools by focusing on screening disputes (vs. tickets, parking, or MTD answers). An agent can immediately tell what this tool does and when it applies without ambiguity.

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 conveys its purpose clearly but does not explicitly discuss when to use it versus alternatives (e.g., denial_clock or parking_route). It relies on the subject matter to distinguish itself, which is sufficient given the distinct sibling names, but it lacks an explicit 'use this when…' or 'for X, use Y instead' statement. The context is implied rather than stated.

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