Lotlytics — US Real Estate Market Data & Investment Analytics

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

With no annotations provided, the description carries the full behavioral disclosure burden. It reveals that an API key with an Investor plan is required, explains how to send the key (X-API-Key header), and describes the nature of the output (head-to-head comparison with winners highlighted across price, yield, appreciation, and more). It does not cover rate limits or failure behavior, but the read-only nature is evident and the essential invocation requirements are disclosed.

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 appropriately sized and front-loaded with the core comparison purpose. The auth guidance is redundant across two sentences ('Requires API key...' and 'Already subscribed? Your key is at...'), but the overall structure is efficient and each sentence adds meaningful information.

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 simple parameter set (four required strings) and the existence of an output schema, the description covers the key contextual needs: what the tool does, when to use it, auth requirements, and a high-level view of the result. The main gap is parameter format guidance, but the output schema fills the return-value details and the tool's complexity is low.

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 0%, so the description should compensate for missing parameter documentation. The parameter names (city_a, state_a, city_b, state_b) are self-explanatory, and the description's 'two real estate markets' phrasing loosely maps to them. However, it does not specify expected formats for city/state values (e.g., full state name vs. two-letter code), leaving some ambiguity for an agent.

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 compares two real estate markets side by side, with a specific verb ('Compare') and resource ('two real estate markets'). It also highlights the head-to-head nature and the 'winners highlighted' output, distinguishing it from sibling tools that likely handle single-market summaries or list/search operations.

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 explicitly says 'Use when deciding between two markets for investment,' providing clear context for when this tool should be selected. It does not explicitly name alternatives or state when not to use the tool, but the use case is specific enough to guide an agent.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly reveals the output shape (score, label, key signals), the market scope, and the access-tier limitation (top 50 vs all 894 metros). It does not mention data freshness or error behavior, but for a simple read-only screening tool this is sufficient and adds value beyond the schema.

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 concise and well-structured: purpose, return value, usage guidance, and access limits are each covered in one short sentence. There is no filler or repetition of schema information. Every sentence earns its place.

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?

The combination of description, output schema, and simple parameters makes the tool adequately understandable. The description provides the important contextual details: when to use it, what it returns, and its coverage limits. A small gap remains on parameter formatting, but this is minor for city/state strings with an output schema present.

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 0% and the description adds no parameter-specific guidance. While 'city' and 'state' are mostly self-explanatory, the description does not specify expected formats (e.g., state abbreviation vs full name, city naming conventions) or that these refer to a metro area. Given the low coverage, the description should compensate but does not.

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 ('Get') and a clear resource ('investment health score (1-10)') for a defined scope ('US real estate market'). It includes the return format (score, label, key signals), which removes ambiguity. It also distinguishes itself from get_market_summary by identifying itself as the quick-screening step.

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 explicitly says 'Use this FIRST for quick screening before digging deeper with get_market_summary.' This tells the agent when to use this tool and directs it to the relevant sibling alternative for deeper analysis. It also provides access-tier guidance (free vs API key), which is a clear usage condition.

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?

With no annotations present, the description carries the full burden and does well by disclosing access tiers: free tier covers top 50 markets, while an API key unlocks all 894 US metros. It also reveals the kind of data returned. It stops short of detailing rate limits or error behavior, but the core behavioral constraints are communicated.

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 well-structured: it opens with the main action, lists outputs, notes tier limitations, and ends with routing advice. Every sentence adds useful information without repetition or 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?

For a simple two-parameter read tool with an output schema, the description is largely sufficient. It covers what the tool returns, access limitations, and the recommended workflow relative to a sibling. The main gap is the lack of parameter format guidance, but this is a minor issue given the task's simplicity.

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 0%, so the description must compensate. It adds minimal meaning by clarifying 'US city or metro area' and referencing US metros, but it does not explain accepted formats for state (e.g., 'CA' vs 'California'), how to represent a metro area, or disambiguation rules. This leaves the two required parameters under-specified.

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 verb ('Get'), the resource ('real estate market summary'), and the scope ('US city or metro area'). It also lists the specific metrics returned, making the tool's purpose highly precise. It distinguishes itself from get_market_health by framing this tool as the 'full picture' version.

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 sequencing: use get_market_health first for a quick score, then use this tool for the full picture. This clearly guides the agent on when to invoke this tool relative to a key alternative, though it does not discuss other siblings like compare_markets or list_markets.

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?

With no annotations, the description carries the full burden and does disclose meaningful behavioral constraints: free tier returns only top 50 US metros, while an API key unlocks all 894 markets. This is substantive context beyond the schema or title.

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?

Three short sentences, each earning its place: the core purpose, the tier behavior, and the filter option. Nothing is redundant or 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?

For a simple list tool with one optional parameter and an output schema, the essential information is present. The only meaningful gap is the absence of a routing note explaining when to prefer search_markets over 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?

Schema description coverage is 0%, so the description must compensate. It does, by explaining that state is an optional filter and by specifying accepted formats: 2-letter abbreviation or full name. This adds real meaning beyond the bare 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 clearly states the verb and resource: 'List available real estate markets.' This is specific and understandable, but it does not explicitly differentiate this tool from the sibling search_markets, so it stops short of a 5.

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 mentions an optional state filter but provides no guidance on when to use list_markets versus search_markets or other sibling tools. An agent is left to infer the intended use case.

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?

With no annotations, the description carries the burden of behavioral disclosure. It adds authentication details (API key required, Investor plan, X-API-Key header) and the no-filters default behavior. It doesn't mention rate limits or read-only nature, but for a search tool the essential behavior is covered.

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 relatively long but each sentence is purposeful: main purpose, auth, examples, filters, default behavior, and key retrieval. It is front-loaded with the core statement and organized with line breaks. Slightly verbose with links but not wasteful.

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, no schema descriptions, and no annotations, the description covers the main use case, examples, auth, and fallback behavior; the presence of an output schema reduces the need to describe return values. Still, it leaves the 'limit' parameter unexplained and does not specify units for several filters, which is a meaningful gap for correct 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?

Schema has 0% description coverage, so the description must compensate. It lists the five filter parameters and gives natural-language examples that clarify some semantics (e.g., 'under $300k' maps to max_price). However, it omits the 'limit' parameter entirely and does not explain units or the meaning of default values for min_appreciation and max_price_to_income.

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 clear verb and resource ('Search for real estate markets') and adds the scope 'matching specific investment criteria.' It is distinguishable from siblings through the emphasis on criteria and the 'No filters' default, though it doesn't explicitly name sibling 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?

Provides practical usage context: a list of filters, natural-language examples, the no-filter fallback behavior, and authentication requirements. However, it does not explicitly state when to prefer this tool over sibling tools like list_markets or compare_markets.

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