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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: 'available-files' lists local resources, 'FLUX_1-schnell-infer' calls a specific AI inference endpoint, and 'search-spaces' performs semantic search on Hugging Face Spaces. There is no overlap in functionality, making tool selection unambiguous for an agent.

    Naming Consistency2/5

    The naming is inconsistent with mixed conventions: 'available-files' uses kebab-case, 'FLUX_1-schnell-infer' mixes uppercase and kebab-case with an underscore, and 'search-spaces' uses kebab-case. There is no predictable verb_noun pattern, and the styles vary chaotically across the set.

    Tool Count3/5

    With only 3 tools, the count feels thin for a server named 'mcp-hfspace' that seems to target Hugging Face Spaces and related resources. While the tools cover distinct areas, the scope might be underdeveloped, lacking operations like managing spaces or handling more inference types.

    Completeness2/5

    Inferred domain includes Hugging Face Spaces and file/resources management, but there are significant gaps: no tools for creating, updating, or deleting spaces or files, and inference is limited to one specific endpoint. This incomplete surface will likely cause agent failures in broader workflows.

  • Average 3.4/5 across 3 of 3 tools scored. Lowest: 2.2/5.

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

    • No community issues in the last 6 months
    • 0 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
  • 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

  • Behavior2/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the endpoint call without explaining what the tool does (e.g., image generation), its effects (e.g., creates an image file), performance traits, or any constraints like rate limits or authentication needs, resulting in insufficient transparency for a tool with multiple parameters.

    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?

    The description is a single, concise sentence that directly states the action. It is front-loaded with no unnecessary words, making it efficient. However, it lacks depth, which is a content issue rather than a structural one, so it scores well for conciseness.

    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's complexity with 6 parameters and no output schema, the description is incomplete. It fails to explain the tool's purpose, behavior, or output, leaving significant gaps. Without annotations or a clear context, it does not provide enough information for effective use, especially compared to sibling tools.

    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?

    Schema description coverage is 100%, providing basic descriptions for all parameters. The description adds no additional meaning beyond the schema, such as explaining parameter interactions or use cases. However, since the schema is fully documented, the baseline score of 3 is appropriate as the description does not compensate but also does not detract.

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

    Purpose2/5

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

    The description 'Call the FLUX.1-schnell endpoint /infer' restates the tool name and title without specifying what the tool does. It mentions an endpoint but lacks a clear verb and resource, such as generating images or processing prompts, making the purpose vague and not distinguishing it from sibling tools like 'available-files' or 'search-spaces'.

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

    Usage Guidelines1/5

    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. The description does not mention any context, prerequisites, or exclusions, leaving the agent with no information on appropriate usage scenarios or how it differs from sibling tools.

    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 of behavioral disclosure. It describes the return format (markdown table with specific fields) which is valuable, but doesn't mention important behavioral aspects like whether this lists all files or has pagination, if it requires authentication, or any rate limits. It adds some context but leaves 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?

    The description is efficiently structured in two sentences: the first states the purpose and usage context, the second specifies the return format. Every sentence adds value with no redundant information, making it appropriately sized and front-loaded.

    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 simplicity (0 parameters, no annotations, no output schema), the description provides sufficient context about what the tool does, when to use it, and what it returns. However, it could be more complete by explicitly differentiating from sibling tools and mentioning any behavioral constraints like access limitations.

    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 tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the lack of parameters. The description appropriately doesn't add parameter information beyond what's in the schema, maintaining focus on the tool's purpose and output. This meets the baseline expectation for a zero-parameter tool.

    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's purpose: listing available files and resources with specific attributes. It uses the verb 'returns' and specifies the resource type ('files and resources'), but doesn't explicitly differentiate from sibling tools like 'search-spaces' which might have overlapping functionality.

    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 guidance on when to use this tool: when the user requests specific resources like 'most recent image' or 'the audio'. However, it doesn't explicitly state when NOT to use it or mention alternatives among the sibling tools, leaving some ambiguity about tool selection.

    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 full burden. It discloses key behavioral traits: the search is semantic (not keyword-based), results come in markdown table format, and the agent should present all results and await Person's guidance. However, it doesn't mention rate limits, authentication requirements, or what happens with empty/no results.

    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 appropriately sized and front-loaded: first sentence states core purpose, second adds query guidance, third specifies output format, fourth provides workflow instructions. Every sentence earns its place with no wasted words or 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?

    Given 1 parameter with full schema coverage and no output schema, the description provides good context about the search approach, result format, and agent workflow. It could be more complete by addressing edge cases (no results, error handling) or explaining the semantic search mechanism, but covers the essential usage scenario adequately.

    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?

    Schema description coverage is 100% (the single parameter 'query' is fully described in schema), so baseline is 3. The description adds marginal value by suggesting query length (3-7 words) and content (task/activity description), but doesn't provide syntax examples or format details beyond what the schema already states.

    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 ('semantic search'), target resource ('endpoint on the Hugging Face Spaces service'), and distinguishes from siblings by focusing on search rather than file listing or inference. It explicitly mentions what the tool does: finding endpoints via semantic search with results in markdown table format.

    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 for when to use this tool: when the Person has a task/activity description (3-7 words) and needs to find relevant endpoints. It instructs to present all results and await further guidance, establishing a workflow. However, it doesn't explicitly mention when NOT to use it or name specific alternatives among siblings.

    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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