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bStyler

Loom Transcript MCP

by bStyler
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JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.5

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one retrieves comments and the other retrieves transcript text from a Loom video URL. There is no overlap or ambiguity between them, as they target different data types from the same resource.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with 'get' as the verb and descriptive nouns ('LoomComments', 'LoomTranscript'). The naming is uniform and predictable across the tool set.

    Tool Count2/5

    With only 2 tools, the server feels thin for a transcript-focused domain, lacking operations like search, update, delete, or other common transcript management functions. This minimal set may limit agent capabilities for comprehensive workflows.

    Completeness2/5

    The tool set is severely incomplete for a transcript domain, offering only retrieval functions without create, update, delete, or search capabilities. This creates significant gaps that could lead to agent failures when trying to perform full lifecycle operations.

  • Average 2.9/5 across 2 of 2 tools scored.

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

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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 provided, the description carries the full burden of behavioral disclosure. While 'Get comments' implies a read operation, it doesn't specify authentication requirements, rate limits, error conditions, or what format the comments are returned in. This leaves the agent with insufficient information about how the tool behaves.

    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, clear sentence that efficiently communicates the core functionality without any wasted words. It's appropriately sized and front-loaded with the essential information.

    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?

    For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what format the comments are returned in, whether authentication is required, or how to handle different video states. Given the lack of structured information elsewhere, the description should provide more context.

    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 schema description coverage is 100%, with the single parameter 'videoUrl' well-documented in the schema. The description doesn't add any additional semantic context beyond what the schema already provides, so it meets the baseline for high schema coverage.

    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 action ('Get comments') and target resource ('from a Loom video URL'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling tool 'getLoomTranscript', which would be needed for a perfect score.

    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 alternatives, nor does it mention any prerequisites or context for usage. With a sibling tool 'getLoomTranscript' available, this represents a significant gap in helping the agent choose appropriately.

    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, so the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't add context beyond that—missing details like authentication needs, rate limits, error handling, or response format. This leaves significant gaps for a tool that likely interacts with an external API.

    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, efficient sentence that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance.

    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 lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like how the transcript is returned, potential errors, or API constraints. For a tool that likely involves external data retrieval, more context is needed to ensure proper usage.

    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 schema description coverage is 100%, with the single parameter 'videoUrl' well-documented in the schema. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, so it meets the baseline for high schema coverage without compensating further.

    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 verb ('Get') and resource ('transcript text from a Loom video URL'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from its sibling tool 'getLoomComments', which likely retrieves comments rather than transcripts, so it misses full sibling differentiation.

    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 alternatives, such as the sibling 'getLoomComments'. It lacks context on prerequisites, exclusions, or scenarios where this tool is preferred, leaving usage decisions unclear.

    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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