Cook County / Chicago Property Data

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

Annotations already indicate safe, read-only, idempotent behavior. The description adds valuable context: monetary cost ($0.10 per call), derived nature, and output type (low/median/high price range). No contradictions with annotations.

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 consists of two efficient sentences. The first sentence front-loads the core purpose and constraints; the second adds cost and an alternative. No wasted words.

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 no output schema, the description covers purpose, constraints, cost, and alternative. It mentions the derived price range but could be more explicit about the output structure (e.g., list of comps). Still fairly complete for a single-parameter tool with strong annotations.

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 a detailed description for the pin parameter. The main description adds no additional parameter semantics beyond what the schema provides, so a baseline score 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 clearly states the tool finds comparable sales in the same neighborhood and property class for a given PIN, with a derived price range. It distinguishes from raw open-data queries and sibling tools by highlighting its automated valuation and cost, making the purpose specific and unambiguous.

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 advises trying get_free_sample first as an alternative, providing clear context for when to use this paid tool. It contrasts with raw queries but does not explicitly list when not to use it or provide a comprehensive decision tree for 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?

Annotations already state readOnlyHint=true, openWorldHint=true, etc. The description adds the cost ($0.01 per call) and the list of returned fields, which provides additional context beyond the annotations. However, it does not elaborate on other behavioral aspects like rate limits or error handling.

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-structured sentence that efficiently conveys the tool's purpose, input requirement, output contents, and cost. No extraneous words or redundant 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?

For a simple tool with one parameter and no output schema, the description lists key returned fields and the cost, providing a good overview. However, it lacks specifics on output format or behavior for invalid inputs, which would be needed for complete understanding.

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% coverage with a detailed description of the pin parameter. The main description only repeats that the PIN is 10 or 14 digits, adding no new semantic information 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 retrieves a Cook County parcel record for a 10- or 14-digit PIN and lists the specific data fields returned (address, assessor class, township, etc.). This specific verb+resource combination distinguishes it from siblings like search_chicago_property_by_address, which handles address-based lookups.

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 no guidance on when to use this tool versus its siblings. It mentions the cost but does not specify conditions for choosing this tool over alternatives like get_cook_county_property_dossier or find_chicago_comparable_sales.

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 indicate readOnly, openWorld, idempotent, non-destructive. Description adds value by explaining permit linking derivation, cost ($0.03), and that result is a finished record not reproducible elsewhere. No contradiction.

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?

Compact single paragraph, front-loaded with purpose, every sentence adds value (what's included, uniqueness, cost, prerequisite). No wasted words.

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?

Covers key aspects: data contents, permit linking quirk, cost, prerequisite call. No output schema means agent lacks exact structure, but description of contents is sufficient for selection. Could add more on expected response format.

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?

Single parameter pin is fully documented in schema (regex, format). Description adds context: PIN digit length, dashes allowed, and recommends search_chicago_property_by_address if only address is available, improving usability.

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?

Clearly states it returns a full property dossier with specific data types (parcel basics, sales, deeds, permits, tax, location). Distinguishes from siblings by noting it's the 'one-call due-diligence record' and permits are uniquely linked to PIN, not reproducible via raw data queries.

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?

Explicitly says to use PIN and provides alternative address lookup tool if needed. Implicitly frames this as comprehensive research tool, but lacks explicit when-not-to-use or trade-offs vs 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?

Annotations already declare readOnlyHint, idempotentHint, and no destructiveness. The description adds that the tool is free, returns a fixed representative example, and its purpose is validation. This provides behavioral context beyond annotations, though it does not detail any limitations like synthetic data.

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 sentences, front-loaded with the key feature 'FREE ($0, no payment)', and every word serves a purpose. It is highly concise and well-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?

Given no output schema, the description explains the purpose and what the sample covers (every paid response shape). It is complete enough for a simple sample tool, though it could specify if the sample data is synthetic or real.

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 no parameters and schema coverage is 100%. The description does not need to explain parameters. According to the rubric, 0 parameters warrants a baseline score of 4.

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 provides a free sample of all paid response shapes to validate data structure and quality. It uses specific verbs ('get', 'validate') and distinguishes itself from sibling tools which are paid and return specific data types.

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 'Call this FIRST to validate the data structure and quality before spending anything.' This provides clear guidance on when to use it. It could mention alternatives but the context implies this is the preliminary step before using any paid sibling 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 mark readOnly, openWorld, idempotent, non-destructive. Description adds useful context: output shape (ranked candidates with address, city, ZIP, match score), workflow guidance, and pricing. No contradictions with annotations.

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 sentences: first sentence defines purpose and output format, second sentence provides workflow and cost. No unnecessary words, front-loaded with key info.

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 simple tool with one parameter, good annotations, and no output schema, the description fully explains what it does, how to use it in a workflow with siblings, and cost. No gaps.

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?

Only one parameter 'address' with schema description already covering full/partial address and minimum length. Description repeats schema info and adds an example, but does not significantly increase meaning beyond the schema's 100% coverage.

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?

Description states it resolves a Cook County/Chicago address to parcel PIN(s) with ranked candidates, clearly distinguishing from siblings by specifying this is the first step when you have an address but not a PIN.

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?

Explicitly instructs to call this first when address is known but PIN is not, then pass the PIN to get_cook_county_parcel, get_cook_county_property_dossier, or find_chicago_comparable_sales. Also notes cost per call.

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