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jshsakura

a360-mcp

by jshsakura

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clear, distinct purpose: get_bot_actions retrieves bot action definitions, get_execution fetches a single execution's details, and list_executions searches execution history. There is no ambiguity or overlap between these operations.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern, using get_ for singular resources and list_ for collections. The naming is predictable and adheres to standard conventions.

    Tool Count4/5

    With only 3 tools, the server is at the lower end of the typical range, but each tool covers a distinct aspect of the domain (bot actions and executions). It feels slightly thin but is still reasonable for a focused utility.

    Completeness2/5

    The server lacks essential operations such as listing bots (making it impossible to discover bot IDs for get_bot_actions) and does not support execution lifecycle actions like starting or canceling executions. This creates significant gaps for agents trying to perform broader workflows.

  • Average 3.3/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 15 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
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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 disclosing behavioral traits. It only mentions the HTTP method and endpoint, but fails to state that this is a read-only operation, what data is returned, whether pagination applies, or any potential side effects. This is insufficient for an agent to understand the behavior beyond the raw action.

    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 with no filler. Every word contributes to identifying the tool's function. It is concise and well-structured for a simple action.

    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 no output schema, no annotations, and a terse description. It does not explain what an 'execution history' entry contains, whether results are paginated, or how this relates to sibling tools. Given the lack of structural metadata, the description fails to provide sufficient context for an agent to confidently use the tool.

    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 67%, with descriptions for status and deployment_id. The limit parameter is partially described via title, default, min, and max, but no explicit purpose is given. The tool description itself adds no parameter information, but the schema provides moderate clarity. Given medium coverage, the description does not compensate or add meaning, so a mid-range score is appropriate.

    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 function: 'Search execution history' with a specific verb and resource. It also mentions the exact endpoint (POST /v3/activity/list), adding technical specificity. However, it does not explicitly differentiate from sibling tools like get_execution, though 'search' vs 'get' implies a difference.

    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?

    No guidance is provided on when to use this tool versus alternatives like get_execution or get_bot_actions. The description only states the action without any exclusions, prerequisites, or comparisons. The intended use is implied by the name but not explicitly communicated.

    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, the description must carry the full burden. It only states the action ('Fetch') and the returned fields, offering no insight into potential side effects, error behavior, or permissions. The description is minimal and adds little beyond what the name implies.

    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 front-loads the essential information. Every word earns its place with no redundancy.

    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 fetch tool with a well-defined schema, the description provides adequate high-level context (what is returned) but omits details about response format, error handling, or source of execution_id (though the schema covers the latter). The absence of an output schema and annotations means more could be explained, but the tool's simplicity keeps the gap modest.

    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 fully describes the only parameter (execution_id) with a note distinguishing it from deploymentId, giving 100% schema coverage. The description adds no extra parameter semantics, so the baseline 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 uses a specific verb ('Fetch') and clearly identifies the resource ('one execution') and the specific returned fields ('status, message and error detail'). This distinguishes it from sibling tools like 'list_executions' (multiple) and 'get_bot_actions' (different resource).

    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?

    No explicit guidance is provided on when to use this tool versus alternatives. The singular 'one execution' implies it is for individual lookup, but no mention of when to prefer 'list_executions' or avoid this tool is stated.

    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 must carry the transparency burden. It discloses the output is parsed rather than raw JSON, but it does not mention pagination behavior, error conditions, or whether the operation has side effects. For a list operation this is minimal but not misleading.

    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 with zero wasted words. It clearly states the verb, object, and a key qualifier, making it efficient while conveying the core distinction.

    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?

    The tool is simple, but with no output schema or annotations, the description leaves gaps about the return shape, pagination, and error cases. It is enough for basic selection but not fully complete for calling the tool correctly.

    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 coverage is 50%: file_id is described, but limit has only numeric constraints with no semantics. The description does not clarify how limit applies (e.g., number of nodes returned) and provides no additional meaning beyond the schema.

    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 ('List') and a clear resource ('a bot's action nodes') while adding a distinguishing qualifier ('parsed, not the raw JSON'). This differentiates it from sibling tools related to executions (get_execution, list_executions).

    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 'not the raw JSON' hint implies that this tool is for parsed action nodes, but it does not explicitly name alternatives or state when to choose this over get_execution/list_executions. The guidance is implied rather than explicit.

    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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