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vladthecto

hermes-marketplace-tools

by vladthecto
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.0.2

  • Disambiguation5/5

    Each tool targets a distinct function: product details (get_product_card), reviews (get_reviews), and search (marketplace_search). There is no overlap or ambiguity.

    Naming Consistency4/5

    Two tools follow a 'get_' pattern, but 'marketplace_search' deviates slightly by being noun_verb. The inconsistency is minor and readability remains high.

    Tool Count4/5

    Three tools is a reasonable number for a focused marketplace-browsing server. The scope is narrow but well-defined; no tool feels superfluous.

    Completeness3/5

    The set covers search, product card retrieval, and reviews, but lacks mutation operations (e.g., add to cart, compare) and entity listing (e.g., categories). Gaps exist but core browsing workflows are covered.

  • Average 3/5 across 3 of 3 tools scored. Lowest: 2.4/5.

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

    • No community issues in the last 6 months
    • 4 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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  • 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

  • Behavior2/5

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

    With no annotations, the description must disclose behavioral traits. It only states the tool fetches product reviews, omitting details like pagination (limit parameter), sorting behavior (sort parameter), error handling, or rate limits.

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

    Conciseness3/5

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

    The description is very short (three words), which is concise but too sparse. It lacks critical details that would make it helpful, falling short of earning its place as the sole explanatory text.

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

    Completeness2/5

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

    Given the tool has 4 parameters (2 required), a sort enum, a default limit, and an output schema, the description is insufficient. It does not explain parameter usage, output structure, or behavior, making it incomplete for effective agent invocation.

    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?

    Schema coverage is 0%, so the description must compensate. It provides no information about the four parameters (sort, limit, id_or_url, marketplace), such as what values are valid or how they affect results.

    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 'Product reviews' clearly indicates the resource (reviews) and implies the verb 'get' from the tool name. It distinguishes from siblings like get_product_card (product details) and marketplace_search (searching). However, it does not explicitly differentiate usage scenarios.

    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 guidance is provided on when to use this tool versus alternatives (e.g., get_product_card for product info, marketplace_search for discovery). No context about prerequisites or limitations.

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

  • Behavior2/5

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

    No annotations are provided. The description only lists what the card includes, with no mention of permissions, side effects, rate limits, or response format. Minimal behavioral disclosure.

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

    Conciseness3/5

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

    Single short sentence; concise but lacks necessary details. Could be expanded without becoming verbose.

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

    Completeness2/5

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

    Given no output schema, no annotations, and undocumented parameters, the description fails to provide sufficient context for correct usage. Missing return format, parameter constraints, and behavioral notes.

    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?

    Schema has 0% description coverage. The description does not clarify the parameters: 'id_or_url' could be ambiguous (ID or URL?), and 'marketplace' values are unspecified. No parameter guidance beyond schema.

    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 a full product card with characteristics, description, and image URLs. It uses specific verb-resource phrasing and distinguishes from sibling tools (get_reviews for reviews, marketplace_search for search).

    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?

    Usage is implied: use when needing full product details. However, no explicit guidance on when not to use or alternatives beyond sibling tool names.

    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 full burden. It mentions normalized results and implies that multiple queries are needed for coverage. However, it does not disclose pagination, sorting, rate limits, or whether the search is case-sensitive.

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

    Conciseness4/5

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

    Two sentences, both meaningful: first states purpose, second gives usage advice. No fluff, but could be slightly more structured with parameter details.

    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 moderate complexity (6 params) and presence of output schema, the description covers main purpose and usage strategy but lacks parameter documentation and behavioral details like pagination or result ordering.

    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%, and the description does not explain any of the 6 parameters. Only 'brand' is hinted at via 'с брендом'. The agent must rely on parameter names alone, which may be insufficient for correct invocation.

    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 searching for products on Ozon and/or Wildberries with normalized output. It uses specific verbs and resources, distinguishing it from siblings like get_product_card and get_reviews.

    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?

    Provides explicit guidance to formulate multiple queries with different brands and formulations for better coverage, and to compare results. While it doesn't explicitly mention when not to use or name alternatives, the strategy is clear and useful.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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