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

With no annotations provided, the description carries the full burden. It discloses that computation is deterministic, uses exact formulas identical to the underwriting pipeline, returns a verdict, key metrics, and a summary, and includes disclaimers about the preliminary nature. This is unusually thorough and transparent for a tool definition.

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 longer than average but every sentence earns its place—purpose, usage, inputs, outputs, and disclaimers. It is front-loaded with the core purpose and usage, and the structure flows logically. It could be slightly tightened, but it is not padded.

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 the tool's complexity (9 parameters, 3 deal types, multiple output metrics), the description is remarkably complete. It covers when to use it, what inputs are needed (including the context-sensitive arv_or_value), what the output looks like (verdict, metrics, summary), and the caveats (preliminary screen). No output schema exists, but the description adequately covers return values. There are no significant gaps for an agent to call it 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?

Although schema coverage is 0% (the description does not repeat schema constraints), it adds contextual meaning: it lists all required and optional parameters and clarifies that arv_or_value varies by deal type (ARV for FF, refinance value for BRRRR, sellout for NC). It also explains the returned metrics, which indirectly clarifies parameter roles. This goes beyond the raw schema, though it stops short of detailing each parameter's individual semantics.

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 opens with a clear verb and resource: 'Run a deterministic, lender-grade quick check on a real estate deal.' It then lists concrete use cases (works, pencils, max offer, etc.) and explicitly differentiates from the sibling methodology_faq, which is for general questions. This leaves no ambiguity about what the tool does or how it differs from alternatives.

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 provides explicit when-to-use guidance (specific property/deal questions) and when-not-to-use guidance (methodology, pricing, output formats), naming the alternative tool (methodology_faq) and even stating that results are preliminary and not an appraisal or lender commitment. This fully equips an agent to route correctly.

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