Lotlytics — US Real Estate Market Data & Investment Analytics

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

Annotations already cover read-only, idempotent, and non-destructive behavior, lowering the burden on the description. The description adds useful context beyond annotations: the Investor plan API key requirement, links to get the key, and the output characteristic of marking a winner on price, yield, and appreciation.

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 core purpose is front-loaded in the first sentence, followed by necessary auth guidance and a concrete example. The URLs add length but are operationally relevant, so the description remains efficiently structured.

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 straightforward four-parameter comparison tool with an output schema present, the description supplies purpose, result semantics, authentication requirements, and a worked example. There is no critical missing information for an agent to invoke 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?

Schema description coverage is 100%, and each parameter already has clear descriptions with examples. The description's example reinforces the expected format but adds no substantive meaning beyond what the input schema provides, so the baseline of 3 is appropriate.

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 ('Compare'), a specific resource ('two US markets side by side'), and a distinctive behavior ('winner marked on price, yield and appreciation'). It is immediately distinguishable from siblings like get_market_health, get_market_summary, list_markets, and search_markets.

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 the use case: head-to-head comparison of exactly two markets. It does not explicitly name alternatives or exclusions, but the purpose is specific enough that an agent can infer when to use this tool over the siblings.

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?

The annotations already declare this as read-only, idempotent, and non-destructive. The description adds useful behavior beyond annotations by explaining that the result includes a score, a label, and the signals driving the assessment, and that it is scoped to US markets. No contradictions with annotations exist.

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: it states the output type, label options, and underlying signals in the first sentence, and the example adds concrete input guidance. There is no redundant or filler content.

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 read-only, two-parameter tool with a full input schema and an output schema, the description provides enough context to understand the purpose and expected invocation. It would be more complete if it noted when to prefer this tool over the sibling market tools, but nothing critical for calling it is missing.

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%, with both city and state already well described including case-insensitivity and the need for state due to repeating city names. The description's Tampa/FL example is consistent but does not add substantive parameter semantics beyond what the schema already provides.

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 that the tool returns a 1-10 investment health score with a label and supporting signals for a US market. It is specific about the resource and output, but it does not explicitly differentiate itself from sibling tools like get_market_summary or compare_markets.

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 an example of city and state inputs but provides no guidance on when to use this tool versus its siblings. There is no mention of alternatives, exclusions, or conditions that would help an agent decide between get_market_health and the other market-related tools.

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, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context by enumerating the returned metrics (median price, appreciation, rental yield, momentum, migration). There is no contradiction with annotations, and no hidden side effects are implied.

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 dense sentences with no filler. The purpose is front-loaded, and the example earns its place by illustrating both valid input and expected output.

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 strong annotations, full schema parameter coverage, and presence of an output schema, the description provides nearly everything needed to invoke the tool correctly. The only notable gap is explicit guidance on when to use this tool instead of its sibling market tools.

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 documents both parameters fully (100% coverage), including examples and case-insensitivity. The description adds value with a concrete Austin/TX example that shows how city and state combine and what kind of output results, going beyond the schema without duplicating it.

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 names a specific verb and resource: it 'returns [a] full market report for one US city or metro.' The example ('Austin' / 'TX' returning median price, appreciation, rental yield, momentum, and migration) concretely establishes what the tool does and distinguishes it from sibling comparison/listing/search tools.

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 signals that the tool is for a single city or metro query, and it explains why state is required ('city names repeat'). However, it does not explicitly name alternatives or state when to prefer compare_markets, list_markets, or search_markets, so it stops short of full routing guidance.

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, openWorldHint, idempotentHint, and non-destructive behavior. The description adds useful context about server-specific market availability and state filtering, which is meaningful beyond the structured annotations and not contradicted by them.

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?

Two tight sentences, with the core action and scope front-loaded and a helpful example in the second sentence. No filler or redundant restatement of the title.

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 simple read-only enumeration tool with one optional parameter, an output schema, and clear safety annotations, the description is complete. It tells the agent what the server can report on and how to narrow results, and the output schema removes the need to describe return shape.

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%, with the state parameter already documented as an optional filter with an 'TX' example. The description's 'state=\'TX\'' example adds no substantive meaning beyond the schema, so the baseline score of 3 applies.

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: 'List the US markets this server can report on', with an optional state filter. It is clear about scope but does not explicitly differentiate itself from the sibling tool search_markets, so it stops short of full sibling differentiation.

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 implies a use case: enumerate available US markets, optionally narrowed to one state. However, it provides no explicit guidance about when to prefer list_markets over search_markets or the other market tools, leaving the routing decision mostly to inference.

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 mark the tool as read-only, idempotent, and non-destructive. The description adds meaningful behavior beyond those annotations: it requires an API key on the Investor plan and provides explicit URLs for pricing and key creation. It also documents the 'no filters returns national top-ranked markets' behavior, which is useful and non-obvious.

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 behavior, followed by auth requirements and a useful example. The two URLs are somewhat clunky but earn their place because they provide necessary setup instructions. No filler sentences are present.

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 six optional parameters, a complete input schema, an output schema, and safety annotations, the description covers the essential operational details: ranking behavior, national default, API key requirement, and a representative parameter combination. Nothing critical is missing 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 already documents all six parameters with descriptions and defaults, so schema coverage is 100%. The description contributes a practical example state='TX', max_price=300000, min_rental_yield=6, but it does not add new semantic meaning beyond what the schema already provides. Baseline 3 is appropriate.

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 action and resource: 'Rank US markets by investment criteria.' It also clarifies that omitting filters returns top-ranked national markets, which distinguishes it from a simple listing tool. However, it does not explicitly name or differentiate against sibling tools like list_markets, so it falls just short of the strongest clarity.

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 implies when to use the tool: when you want markets ranked by investment criteria, optionally filtered by state and metrics. It gives a concrete example, but it does not explicitly explain when to prefer compare_markets, get_market_health, or list_markets instead. No exclusions or alternative routing is provided.

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