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LEOyrh

UrbanKit County Parcel Atlas

by LEOyrh

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.4

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: building a query URL, fuzzy-matching counties, retrieving endpoint details, and listing counties. No functional overlap exists.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern (build_owner_query, find_county, get_parcel_endpoint, list_counties), making the tool surface predictable.

    Tool Count4/5

    With only 4 tools, the set is minimal but well-scoped for the domain of parcel atlas lookups. No redundant tools exist, though a few more could be added for direct query execution.

    Completeness4/5

    The tools cover the core workflow: locate a county, get endpoint details, build a query, and list counties. A minor gap is the lack of a tool to directly execute the query, but the constructed URL enables external fetching.

  • Average 4.2/5 across 4 of 4 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • No commit activity data available
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior3/5

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

    No annotations are present, so the description must carry the burden. It lists what is returned but does not explicitly state that the tool is read-only or disclose any side effects, performance characteristics, or requirements. The description is adequate but not exhaustive.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single sentence that efficiently enumerates all key outputs without redundancy. It is front-loaded and every element provides value.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the lack of an output schema, the description adequately lists all expected return values. It could be strengthened by noting input validation or error handling, but is complete enough for a simple lookup tool.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has 100% coverage with descriptions for both state and county. The description does not add additional meaning beyond what the schema provides, meeting the baseline for high coverage.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the specific outputs: ArcGIS REST service URL, layer index, searchable field names, owner field, sample query, and UrbanKit deep-link for a county. It distinguishes from siblings like build_owner_query and find_county by focusing on endpoint retrieval.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies usage when a parcel endpoint for a specific county is needed, but does not explicitly state when not to use it or mention alternatives. Siblings (build_owner_query, find_county) suggest a workflow, but no direct guidance is provided.

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

  • Behavior3/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool performs fuzzy matching and returns specific data, which is transparent about its output. However, it does not disclose whether the tool is read-only, whether it requires authentication, or any other behavioral traits.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, well-structured sentence that efficiently conveys the purpose, input format, and return value. No unnecessary words or repetition.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a simple lookup tool with one parameter and no output schema, the description is sufficiently complete. It explains the input and output clearly. However, it could be more complete by mentioning any prerequisites or common errors.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema coverage is 100%, so the schema documents the parameter 'query' with a description. The tool description adds value by providing examples and clarifying the fuzzy-matching behavior, which goes beyond the schema's static description.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states that the tool performs fuzzy matching to find a county by name or FIPS code, and lists the specific information returned (endpoint URLs, fields, etc.). It distinguishes itself from siblings like list_counties by focusing on lookup rather than listing.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides usage examples and input formats (e.g., 'Kane IL', FIPS code), which helps the agent understand when and how to use it. However, it does not explicitly state when not to use it or compare to alternatives like list_counties.

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

  • Behavior4/5

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

    With no annotations, the description carries full burden. It clearly discloses the query uses UPPER and LIKE for case-insensitive partial matching, and references a 'verified owner/taxpayer field' per county. This is sufficient to understand the tool's internal operation and side-effect-free nature.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Two sentences: first states the action and result, second details the query mechanism. Every word is purposeful with no redundancy or extraneous information.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The description adequately covers what the tool does, how it works, and what it returns. It leverages the context of county-specific fields. For a URL builder with three well-documented parameters and no output schema, it is nearly complete; minor omission is potential limitations (e.g., URL length, ArcGIS version compatibility).

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    All three parameters have 100% schema coverage, but the description adds value by explaining the SQL-like query pattern (UPPER... LIKE) applied to owner_name, which goes beyond the schema's 'partial match, case-insensitive' description. This enhances understanding of how the parameter is used.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description uses a specific verb ('constructs') and identifies the resource ('ArcGIS REST query URL'), clearly stating it builds the exact URL for owner name queries. It distinguishes from sibling tools (find_county, get_parcel_endpoint, list_counties) by focusing on URL construction for owner queries.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description explains the tool returns a URL for browser or direct fetch, implying its use for querying by owner name. It also details the query pattern (case-insensitive partial match), giving guidance on behavior. However, it lacks explicit when-not-to-use or alternatives, though the context of siblings provides some differentiation.

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

  • Behavior4/5

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

    With no annotations provided, the description fully carries the transparency burden. It discloses that only counties with verified endpoints are returned, and mentions the approximate count (155). No side effects or auth requirements are needed for a read-only list tool.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Two concise sentences: first declares the main function, second explains the optional filter. No redundant information.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given one optional parameter, no output schema, and no annotations, the description covers the tool's purpose, filtering, and scope. It could mention the return format (e.g., list of county names or IDs) but the core functionality is clear.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100%. The description adds value by clarifying that the 'state' parameter accepts both abbreviations and full names, and that omission lists all. This goes slightly beyond the schema's own description.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool returns all counties in the UrbanKit Atlas with verified ArcGIS REST parcel endpoints. It uses a specific verb ('Returns') and distinguishes from siblings like 'find_county' and 'get_parcel_endpoint'.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides explicit usage instructions: pass a state abbreviation or name to filter, or omit to list all ~155 counties. It does not compare to sibling tools but implies when to use state filtering.

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

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