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Server Quality Checklist

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  • Latest release: v0.1.7

  • Disambiguation5/5

    Each tool has a clearly distinct role: authentication, task creation, task status retrieval, and pricing lookup. No overlap or ambiguity between them.

    Naming Consistency4/5

    Most tools follow a verb_noun pattern (audio_to_video, get_task, check_pricing), but 'login' is a standalone verb, creating a minor inconsistency. Still, the naming is clean and predictable overall.

    Tool Count5/5

    With only 4 tools, the server is tightly scoped to its purpose of managing InfiniteTalk tasks via RunAPI. Every tool serves a necessary function without bloat.

    Completeness4/5

    Core lifecycle is covered: create task, check status, and get pricing. Missing cancellation or task listing, but those are minor gaps for a simple workflow.

  • Average 3.5/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • 11 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under Apache 2.0.

  • 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

  • Behavior1/5

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

    With no annotations, the description is the sole source for behavioral traits. It only states the function without disclosing any side effects, return format, or permissions needed.

    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, concise sentence that efficiently communicates the tool's primary purpose.

    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?

    For a simple lookup tool with optional parameters and no output schema, the description is adequate but could improve by hinting at the output structure or units.

    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 coverage is 100% with all parameters described and enumerated. The description adds no additional meaning beyond the schema, meeting the baseline.

    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 action ('look up') and resource ('RunAPI pricing for the infinitetalk model line'), distinguishing it from sibling tools like audio_to_video (a different action) and get_task.

    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 does not provide any guidance on when to use this tool vs alternatives, nor does it mention prerequisites or when not to use it.

    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. It mentions return values (task id, status, output URLs) but does not disclose that this is an asynchronous task creation that may require polling or cost implications, nor how 'wait' and timeouts behave.

    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 sentence that is front-loaded and to the point, but it contains a minor grammatical error ('a InfiniteTalk') and omits details that would require additional sentences.

    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 10 parameters, no annotations, and no output schema, the description is significantly under-specified. It provides a high-level purpose but lacks guidance on parameter usage, task lifecycle, error handling, or how to retrieve results via sibling tools.

    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 only 20% (only 'model' and 'wait' have descriptions). The description does not explain any parameters beyond the 'audio to video' phrase, which hints at the purpose but not the exact param formats or meanings.

    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 creates an InfiniteTalk task on RunAPI for audio-to-video conversion, and specifies return values. This clearly differentiates it from sibling tools like get_task and check_pricing.

    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 by naming the operation and resource, but it does not explicitly state when to use this tool versus alternatives, nor does it mention any prerequisites or conditions.

    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, the description carries the full burden. It discloses the interactive browser flow and config file writing, which is adequate. However, it omits potential failure modes (e.g., no browser available), side effects (overwrites existing config), or that user interaction is required.

    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?

    A single well-structured sentence conveys the core purpose and method. Every word adds value with no redundancy or fluff.

    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?

    For a simple login tool with one parameter and no output schema, the description covers the main behavior. However, it could be more complete by mentioning the expected outcome (e.g., 'returns a success message') or what happens if already authenticated.

    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 coverage is 100%, and the description adds no parameter information. The `force` parameter's meaning is already clear from its schema description. Baseline 3 is appropriate since the description does not need to repeat it.

    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 action (authenticate), the target system (RunAPI), and the specific method (PKCE login flow with config file saving). It unambiguously differentiates from sibling tools (audio_to_video, check_pricing, get_task) which are unrelated.

    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 this is the tool to use for authentication but does not explicitly state when to use it or when alternatives might be better. It lacks guidance on prerequisites or context (e.g., 'use this if you need an API key').

    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 the full burden. It discloses that the tool fetches status and result payload, adding basic return-info context. However, it does not describe error behavior, whether the call blocks, authentication needs, or rate limits. The added context is useful but not comprehensive.

    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, focused sentence with no redundant information. It begins with the action and clearly states the object, making it easy to parse. No filler or unnecessary clauses.

    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?

    With only two parameters, no output schema, and a simple retrieval function, the description adequately conveys the return contents (status and payload). It does not elaborate on error scenarios or edge cases, but given the tool's simplicity, this is a reasonable level of completeness.

    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%, with clear descriptions for both task_id and action. The tool description adds no additional parameter meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.

    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 action ('Fetch') and the resource ('current status and latest result payload for a infinitetask task'), which distinguishes it from sibling tools like audio_to_video (which creates tasks) and check_pricing. It is specific and unambiguous.

    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 purpose implies usage for checking task status, and siblings like audio_to_video suggest a create-then-fetch flow, but the description does not explicitly state when to use this tool versus alternatives, nor does it mention when not to use it. Guidance is minimal.

    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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