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Server Quality Checklist

83%
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  • Latest release: v0.1.6

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: get_cadastral_value retrieves valuation data, lookup_by_address searches by address, lookup_by_cadastral gets characteristics by cadastral number, and lookup_by_coords finds objects at a point. No overlap in functionality.

    Naming Consistency4/5

    All tool names use snake_case and follow a verb_by_noun or verb_noun pattern (e.g., lookup_by_address, get_cadastral_value). The slight inconsistency between 'get' and 'lookup' is minor but does not cause confusion.

    Tool Count5/5

    With 4 tools, the server is well-scoped for its purpose—covering key lookup operations for Russian cadastral data. This is within the ideal range of 3-15 tools.

    Completeness4/5

    The tool set covers essential lookups (by address, cadastral number, coordinates, and value). Minor gaps include lack of spatial search by polygon or full property report, but these are reasonable omissions for a focused public data API.

  • Average 3.6/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • 11 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • 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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    }

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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 provided, so the description carries full burden. It discloses that only open data is returned (no owner PII), which is a behavioral trait. However, it does not mention rate limits, authorization requirements, or what happens with invalid numbers, leaving gaps.

    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?

    Three sentences, front-loaded with purpose, no redundant or extraneous content. Every sentence adds value: what it does, input format, output fields, data limitations.

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

    Completeness3/5

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

    For a simple data lookup with 2 parameters and an output schema (not shown), the description covers the main purpose, input format, output types, and data scope. Missing details on the include_geometry parameter and potential error states, but overall adequate for basic understanding.

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

    Parameters2/5

    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 provides format guidance for the required cadastral_number parameter (example and pattern) but does not explain the optional boolean parameter include_geometry. The listed return fields are helpful but not directly linked to the parameters.

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

    Purpose4/5

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

    The description clearly states the tool retrieves public characteristics by cadastral number, including a format example. However, it does not explicitly differentiate from sibling tools like get_cadastral_value, lookup_by_address, or lookup_by_coords which use different input methods.

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

    Usage Guidelines2/5

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

    No explicit guidance on when to use this tool versus alternatives. The description implies usage when you have a cadastral number but does not mention that other input methods are covered by sibling tools, nor does it provide exclusions or prerequisites.

    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?

    With no annotations, the description must fully disclose behavior. It states it returns current value and cached history, and notes limitations on historical data. However, it does not mention whether the operation is read-only, authentication requirements, 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.

    Conciseness5/5

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

    Two sentences: the first concisely states the primary function, and the second adds a crucial limitation. No redundant words, and the structure is front-loaded with essential 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 the single parameter and presence of an output schema, the description covers the core functionality and its limitation. It provides sufficient context for a simple retrieval tool, though it could mention error cases or value format.

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

    Parameters1/5

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

    The only parameter, cadastral_number, has 0% schema description coverage. The tool description does not elaborate on the format, pattern, or example of a valid cadastral number, leaving the agent without necessary guidance.

    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 the current cadastral value and revaluation history for a Russian property by cadastral number. It specifies the resource (cadastral number), the action (return), and the context (tax base). This distinguishes it from sibling tools which are lookup-focused.

    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 mentions the tool is used for property tax base, providing a clear use case. It also notes that a full audit trail requires Pro tools or EGRN extract, guiding agents on when to consider alternatives. However, it does not explicitly contrast with sibling tools like lookup_by_address.

    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 provided, so description carries full burden. Indicates it is a read operation (Searches, Returns). Does not disclose rate limits, caching, or potential side effects, but given the nature it seems safe.

    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?

    Three concise sentences with no waste. First sentence states purpose, second specifies source, third describes output. Front-loaded with key 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?

    Tool is simple and description covers primary behavior. Output schema exists, so return value details are optional. Missing explanation for object_types parameter reduces completeness slightly.

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

    Parameters2/5

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

    Schema coverage is 0%, but description only explains 'limit' (up to `limit` hits). Does not explain 'address' or 'object_types' parameters, leaving ambiguity.

    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?

    Description clearly states verb (Find), resource (Russian cadastral objects), and input (free-text address). Distinguishes from sibling tools (lookup_by_cadastral, lookup_by_coords) by specifying the search method and source.

    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?

    Implies usage when address is available, but does not explicitly mention when not to use or compare with alternatives. Sibling names provide context but no direct guidance.

    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 provided, so description carries full burden. It mentions coordinate system but lacks details on read-only nature, permissions, response format, or pagination. Output schema exists, partially compensating.

    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?

    Three sentences, front-loaded with the main action, no wasted words. Very concise and readable.

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

    Completeness3/5

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

    Given 4 parameters with no schema descriptions and an output schema, the description covers the core operation but omits parameter details. It is adequate but not fully complete for all parameters.

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

    Parameters2/5

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

    Schema description coverage is 0%. The description adds only coordinate system context for lat/lon; it does not explain object_types, buffer_meters, or their defaults. The agent would need to infer parameter usage.

    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 shows Russian cadastral objects at a geographic point using a specific coordinate system. It differentiates itself from siblings by focusing on coordinate-based lookup.

    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 gives a clear use-case ('what's at this dot on the map') and specifies coordinate system, but does not explicitly compare to sibling tools or state when not to use.

    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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