Real Estate Analyzer

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

The description goes beyond the sparse annotations (all false hints) by disclosing that the output is a non-authoritative 'software estimate,' that omitted inputs get documented defaults, that rates must be fractions, and that a shareable report_url is returned. This adds meaningful behavioral context not captured in the structured fields.

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, well-organized paragraph that front-loads the purpose, then covers strategies, the fraction rule, defaults, disclaimer, and free access. Every sentence adds distinct information with no redundancy, making it efficient for an agent to parse quickly.

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 (2 params, one deeply nested inputs object, output schema present), the description covers the main purpose, available strategies, input defaults, output nature, and the report URL. It doesn't need to detail the output schema since that is provided separately, but it gives enough context for correct invocation and expectation-setting.

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 coverage is 100%, and each parameter already has a description in the schema. The description adds a global rule that all rates/percents are fractions and reinforces the default-filling behavior. While much of this is repeated from the schema, the cross-cutting emphasis on fractions is valuable and may prevent common input errors.

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 specific verb ('Underwrite') and resource ('real-estate investment deal'), then lists concrete outputs (score, verdict, cash flow, cap rate, DSCR, stress tests, break-even thresholds, report link). It also enumerates the supported strategies, making its scope clear and distinguishing it from siblings like list_strategies and solve_max_offer.

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 usage when you have a deal and a strategy in mind, and it names the strategies you can pass. It lacks explicit exclusions or references to alternatives (e.g., 'use best_use to pick a strategy'), but the context is strong enough that an agent would know when to invoke this tool.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description goes further: it warns that all rates/percents are fractions, states that omitted inputs are filled with documented defaults and listed in assumptions.estimated_fields, and notes it is free with no key. These are valuable behavioral details beyond what annotations provide.

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 with the core purpose, followed by essential operational guidance (superset input, fractions, defaults, no key). Every sentence contributes meaningful information; there is no fluff or repetition of schema details.

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 complex nested schema and multiple strategies, the description covers key behavior: skipping missing strategies, default handling, fraction convention, and where defaults are reported. An output schema exists, so return structure doesn't need explanation, and the description is complete enough 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?

The input schema has 100% description coverage, so the baseline is 3. The description adds critical global semantics not uniformly present in the schema: sending a superset, all rates being fractions, and omitted fields getting defaults. This elevates the value beyond the structured schema.

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 and resource: 'Screen ONE property across every strategy...' and 'rank them by deal score', directly answering 'what is the best use of this property?'. It distinguishes itself from siblings like analyze_deal (single-deal analysis) and list_strategies (strategy listing).

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?

It clearly instructs to 'Provide a superset of inputs' and explains that strategies missing inputs are skipped with reasons, which is key usage guidance. It doesn't explicitly mention when not to use it or alternative tools, but the 'best use' framing and sibling context make the intended use clear.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description adds value beyond these. It discloses that the tool is 'Free, no key' (no authentication required) and that it lists 'every supported strategy,' indicating a complete enumeration without filtering. This supplements the annotation-provided safety profile.

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 concise sentences that front-load the main action, immediately state the usage recommendation, and add a practical note about cost/authentication. Every sentence provides distinct value, and there is no verbosity or repetition.

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?

This is a simple, parameterless tool with rich annotations (readOnly, idempotent, non-destructive) and an output schema. The description covers the full scope: what it lists, when to use it, and access requirements. No additional context is needed for an agent to correctly select and invoke this tool.

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 tool has zero parameters, and the schema is empty (100% coverage by default). The per-rubric baseline for 0 parameters is 4. The description does not need to explain parameter semantics, but it does clarify what the output contains (required and optional input fields per strategy), which adds useful context.

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: 'List every supported strategy with its required and optional input fields.' The verb 'list' and resource 'strategies' are specific, and the scope 'every supported strategy' distinguishes it from the sibling analysis/optimization tools. It unambiguously describes a discovery/metadata operation.

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 usage guidance: 'Call this first when unsure which inputs a strategy needs.' This establishes a clear use case and priority, though it does not explicitly name alternative tools or exclusion criteria. The guidance is clear and actionable, fitting a score of 4.

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

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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds valuable behavioral context: it fills omitted inputs with the listed defaults, returns the binding constraint, and notes 'Free, no key.' This goes beyond the annotation safety profile.

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 dense but each sentence adds a distinct piece of information: purpose, output, strategies, input usage, targets, fraction convention, default fill behavior, and cost. It is front-loaded with the primary purpose and avoids filler.

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 complexity of the tool (multiple strategies, nested inputs, targets, defaults), the description covers purpose, usage, parameter conventions, default behavior, and output. The presence of an output schema means return-value details are captured there, so the description is complete for 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 covers many parameter descriptions, but the description adds cross-cutting semantics: all rates are fractions, inputs without a price anchor use ARV/asking price, and the targets object can override defaults. This helps the agent set the correct parameter values, especially the nested objects.

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 an explicit verb and resource: 'Reverse-solve the Maximum Allowable Offer: the highest purchase price that still meets every return target.' It further specifies the output (MAO, binding constraint, per-target price ceilings) and lists supported strategies, clearly distinguishing it from siblings like analyze_deal.

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 ('Provide the deal inputs WITHOUT committing to a price') and explains how to override targets. It does not explicitly name alternative sibling tools, but the usage context is unambiguous enough for an agent to select it appropriately.

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