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nod-protocol

nod-mcp-server

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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: check_capability validates a specific action against a business's manifest, while lookup_nod retrieves and summarizes the entire manifest. There is no overlap or ambiguity between them, as one is for targeted validation and the other for general information retrieval.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with snake_case naming: check_capability and lookup_nod. The verbs 'check' and 'lookup' are semantically appropriate and distinct, and the naming style is uniform throughout the set.

    Tool Count2/5

    With only two tools, the server feels under-scoped for its apparent purpose of interacting with NOD Protocol manifests. While the tools cover basic retrieval and validation, the lack of tools for actions like updating manifests, managing policies, or executing supported actions suggests a thin surface that may limit agent functionality.

    Completeness2/5

    The tool set is significantly incomplete for the NOD Protocol domain. It provides read-only access to manifests but lacks tools for creating, updating, or deleting manifests, or for actually executing the supported actions (e.g., order_food, book_appointment). This creates dead ends where agents can inspect but not interact with the business capabilities.

  • Average 4/5 across 2 of 2 tools scored.

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

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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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

  • Behavior4/5

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

    With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it fetches a manifest, reports on support status, endpoint URL, authentication requirements, and policy constraints. This covers critical operational aspects like auth needs and constraints, though it could add details on 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.

    Conciseness5/5

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

    The description is front-loaded and efficiently structured in a single sentence that covers purpose, inputs, and outputs without waste. Every element (e.g., action examples, reported details) serves to clarify the tool's function, making it concise and well-organized.

    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 tool's moderate complexity (2 parameters, no output schema, no annotations), the description is largely complete: it explains what the tool does, what it returns, and key behavioral aspects. However, it could improve by mentioning the sibling tool 'lookup_nod' for better context or detailing output format, though the absence of an output schema makes this less critical.

    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% description coverage, providing clear definitions for 'domain' and 'action'. The description adds minimal value beyond the schema by listing example actions, but it doesn't elaborate on parameter interactions or constraints. Baseline score of 3 is appropriate as the schema does the heavy lifting.

    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's purpose with specific verbs ('fetches', 'reports') and resources ('business's NOD manifest'), and it distinguishes from the sibling tool 'lookup_nod' by focusing on capability checking rather than general lookup. It provides concrete examples of actions like 'order_food' and 'book_appointment' to illustrate scope.

    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 context by specifying it checks 'whether the action is supported' and lists common actions, but it does not explicitly state when to use this tool versus alternatives like 'lookup_nod' or provide exclusions. It offers some guidance through examples but lacks direct comparative instructions.

    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 provided, the description carries the full burden. It discloses the HTTP fetch behavior, URL construction pattern, and return format. However, it doesn't mention error handling, timeout behavior, authentication requirements, rate limits, or whether this is a read-only operation (though implied by 'fetches').

    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 efficiently structured in a single sentence that front-loads the core action and resource, followed by specific return details. Every element (source URL, localhost exception, return structure) serves a clear purpose with zero redundancy.

    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 single-parameter read operation with no output schema, the description provides good context about what gets fetched and returned. However, without annotations or output schema, it could benefit from more detail about error cases or response format specifics to be fully complete.

    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% description coverage, so the baseline is 3. The description doesn't add parameter-specific details beyond what the schema provides (domain format examples are already in schema). It mentions the URL construction but doesn't elaborate on parameter usage beyond the schema's documentation.

    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 action ('fetches'), resource ('business's NOD Protocol manifest'), source URL pattern, and structured return format. It distinguishes from the sibling tool 'check_capability' by focusing on manifest retrieval rather than capability verification.

    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 clear context about when to use this tool (to get a structured summary of business identity, capabilities, actions, endpoints, and contacts) and mentions the alternative server for localhost domains. However, it doesn't explicitly state when NOT to use it or directly compare with the sibling tool 'check_capability'.

    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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