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ytugarev
by ytugarev

Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: send_a2a_message sends messages, get_a2a_task retrieves task state, get_agent_card fetches agent metadata. No overlap in functionality.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with snake_case (get_a2a_task, get_agent_card, send_a2a_message). The naming is predictable and uniform.

    Tool Count5/5

    Three tools is appropriate for a minimal A2A bridge: send message, poll task result, and discover agent capabilities. The scope is well-defined and not over- or under-tooled.

    Completeness4/5

    The set covers core interactions (send, poll, discover) but lacks a cancel or list tasks operation. Minor gap, but agents can work around by polling for completion.

  • Average 4.2/5 across 3 of 3 tools scored. Lowest: 3.4/5.

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

    • No community issues in the last 6 months
    • 5 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?

    No annotations provided, so description carries full burden. It only states the action without disclosing side effects, authentication needs, or behavior on invalid input. The fetch is likely read-only but not explicitly stated.

    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?

    Single sentence, front-loaded verb, no unnecessary words. Highly efficient.

    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?

    Adequate for a simple fetch with one optional parameter and an output schema. However, lacks error handling or availability notes. Minimal but sufficient.

    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%. Description does not add meaning to the parameter 'agent_url' beyond its schema definition (string with default). The description could clarify the format or required permissions.

    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 the verb 'Fetch' and the resource 'capabilities (name, description, skills) of an A2A agent'. It distinguishes from sibling tools which deal with tasks and messages.

    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?

    Implied usage (when you need agent capabilities) but no explicit guidance on when not to use or alternatives. No exclusions mentioned.

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

  • Behavior4/5

    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 retrieves status and output, and that the task continues running server-side. It does not explicitly state it is read-only, but that is implied. The description provides useful context for polling behavior but lacks explicit mention of rate limits or authentication.

    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?

    Two sentences with no wasted words. The first sentence states the purpose, the second provides usage guidance. Information is front-loaded and easy to parse.

    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?

    For a simple fetch tool with two parameters (one required) and an output schema, the description covers the key use case (polling after send_a2a_message failure) and explains how to obtain the required task_id. It is missing agent_url explanation, but given its default and typical usage (same as the original message), the overall completeness is high.

    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 explains the task_id parameter indirectly (derived from error messages or response footer), but does not mention the agent_url parameter at all, which has a default but may need to be overridden. The explanation is insufficient for both 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 starts with a clear verb+resource: 'Fetch the current state and result of a previously started A2A task.' This distinguishes it from sibling tools like send_a2a_message (which starts tasks) and get_agent_card (which retrieves agent information).

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

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly states when to use: 'Use this when send_a2a_message timed out or errored after the task had already started.' It provides context that the task runs server-side and explains how to obtain the task_id from error messages or the response footer.

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

  • Behavior5/5

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

    With no annotations, the description fully discloses behavior: emits progress notifications, may time out but task continues server-side, response format includes an [a2a ...] line. It clarifies that omitting ids starts a fresh task, and describes how to handle timeouts.

    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 concise (approximately 9 lines) and well-structured: purpose first, then response continuation, then timeout handling. Every sentence adds value, no redundancy.

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

    Completeness5/5

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

    Given the tool's complexity (asynchronous task-based communication, with progress notifications and timeout recovery) and the presence of an output schema (though not shown), the description covers all necessary context: usage, continuation, error handling, and ties to sibling tools. It is complete for an agent to use correctly.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema has 0% description coverage; the description adds meaning to all 4 parameters: message as content, task_id/context_id for conversation continuity, and agent_url as default endpoint. It explains how omitting ids vs. providing them changes behavior.

    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 starts with a clear verb-resource pair: 'Send a message to an A2A agent and return its final text response.' It distinguishes from siblings get_a2a_task (retrieve results) and get_agent_card (get metadata) by focusing on initiating or continuing a conversation.

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

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Provides explicit guidance: explains the response format with task_id/context_id, instructs to pass those back to continue the conversation, and advises to tune A2A_TIMEOUT_SECONDS for long-running tasks instead of treating delays as hangs. Also mentions using get_a2a_task if a timeout occurs, linking to the sibling tool.

    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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