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Server Quality Checklist

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  • Latest release: v0.1.0-alpha.7

  • Disambiguation4/5

    Each tool has a distinct purpose: locating the executable, running a script, and verifying FBX re-import. The only slight overlap is that verify_fbx_reimport is a specialized form of run_script, but the descriptions clarify their intended uses.

    Naming Consistency5/5

    All tool names follow a consistent 'blender_<verb>...' pattern (locate, run_script, verify_fbx_reimport). The naming convention is uniform and predictable.

    Tool Count5/5

    With only 3 tools, the set is tightly scoped to Blender automation workflows. Each tool serves a clear and necessary function, and the count is well within the expected range for a focused utility server.

    Completeness3/5

    The toolset covers the core workflow of locating Blender, running scripts, and verifying FBX files, but lacks generic ways to retrieve script output or handle other common Blender operations. This leaves some gaps for broader automation scenarios.

  • Average 3/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 25 commits in the last 12 weeks
    • No stable releases found
    • 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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • This repository includes a glama.json configuration file.

  • This server has been verified by its author.

  • Add related servers to improve discoverability.

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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 carries the full burden of disclosing side effects and runtime behavior. It mentions headless Blender and file I/O, but omits external dependencies, error cases, and what the verification result contains.

    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 with no filler, front-loading the primary action and result. It is appropriately concise for the amount of information it conveys.

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

    Completeness1/5

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

    This is a tool with five parameters, no output schema, and no annotations, yet the description is only a vague one-liner. It does not explain return values, parameter semantics, or the meaning of the verification result, making it insufficient for correct 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 description coverage is 0%, and the description does not mention or explain any of the five parameters. Required fields like fbxPath and optional parameters like resultPath and requiredPrefixes are completely undocumented.

    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 ('Import') and a specific resource ('FBX in headless Blender'), and clearly indicates the JSON verification output. This distinguishes it from siblings like blender_locate and blender_run_script, which target different actions.

    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?

    The description provides no guidance on when to use this tool versus the sibling tools, nor does it mention any alternatives or exclusions. It simply states the action without placement in a workflow.

    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?

    With no annotations provided, the description must fully disclose behavior. It states only that the tool 'resolves' an executable, but does not explain whether it searches system paths, how it handles the optional blenderPath parameter, what happens if Blender is not found, or what the return value looks like. This lack of detail leaves significant behavioral ambiguity.

    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, tightly worded sentence that immediately states the core purpose. It is appropriately sized and front-loaded with the key action ('Resolve'), with no wasted words or redundant detail.

    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?

    The tool has low complexity (one optional parameter, no output schema), making it feasible for the description to be complete. However, it omits crucial details: what the parameter does, what the tool returns, and error behavior. While the purpose is clear, the description is too skeletal for an agent to invoke the tool correctly in a real workflow.

    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 input schema contains one parameter, blenderPath, with no description in the schema (schema coverage 0%). The tool description does not mention this parameter at all, so it fails to explain its purpose (e.g., whether it is an override or a hint). With low schema coverage, the description must compensate, and it does not.

    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 resolves the local Blender executable, using a specific verb ('Resolve') and resource ('local Blender executable'). It distinguishes itself from siblings like blender_run_script and blender_verify_fbx_reimport by focusing on locating the executable rather than executing or verifying.

    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?

    The description provides no explicit guidance on when to use this tool or how it relates to the sibling tools. The phrase 'used for background automation' vaguely implies a setup/prerequisite step, but there is no mention of alternatives, exclusions, or typical workflow placement.

    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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'background mode' but does not disclose potential side effects, output handling, error behavior, timeout implications, or whether the script execution is blocking. This is insufficient for a tool that runs arbitrary scripts and could have significant side effects.

    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, front-loaded sentence that conveys the core functionality without any wasted words. It is appropriately concise for the tool's purpose.

    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 6 parameters, no annotations, and no output schema, the description is incomplete. It does not explain how output is returned, the meaning of timeoutMs, cwd, blenderPath, or outputTailChars, nor does it mention any constraints or side effects. The description provides only a surface-level understanding, which is inadequate for a tool with this complexity.

    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 only mentions 'explicit Python script' and 'optional script arguments', which loosely map to scriptPath and scriptArgs, but it completely omits cwd, timeoutMs, blenderPath, and outputTailChars. The description adds minimal meaning beyond the parameter names and fails to explain the purpose of most parameters.

    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 runs Blender in background mode with an explicit Python script and optional script arguments. It specifies the action (run), the resource (Blender), and the mode (background), which distinguishes it from sibling tools like blender_locate (locating Blender) and blender_verify_fbx_reimport (verifying FBX reimport).

    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 its usage by saying 'Run Blender in background mode with an explicit Python script', but it does not explicitly state when to use this tool versus alternatives or provide any exclusions. There is no mention of prerequisites or conditions for use, so it remains implied rather than explicitly guided.

    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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  • Evaluate tool definition quality.

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