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Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    The three tools have clearly distinct purposes: create, list, and move (status update). There is no overlap in functionality, making it easy for an agent to select the right operation.

    Naming Consistency5/5

    All tool names follow the identical pattern `zentra_task_<verb>` with snake_case. This consistent verb_noun structure makes the API predictable and easy to navigate.

    Tool Count4/5

    At 3 tools, the server is concise but not under-powered for a focused task management use case. The count is within the well-scoped range, though slightly lean.

    Completeness4/5

    The set covers the core lifecycle: creation, listing/filtering, and status transitions. Missing operations like full detail retrieval or deletion are minor gaps that can often be worked around via listing, but a dedicated get/update would improve completeness.

  • Average 3.8/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 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
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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 states that it updates status, without mentioning whether the operation is idempotent, whether status transitions are validated, what happens on invalid transitions, or what is returned. This is insufficient for a mutating tool.

    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 purpose and parameter identification.

    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 is a mutation with no output schema and no annotations, the description is incomplete. It does not explain what the response looks like, possible error conditions, or whether status transitions are restricted. This leaves significant ambiguity for an agent.

    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 0%, so the description must compensate. It mentions 'status' and 'by id', identifying the roles of both parameters. However, it adds no extra meaning beyond the schema's own names and enum, such as transition rules or format expectations.

    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 'Updates an existing task's status by id' clearly specifies the action (updates), the resource (task), the attribute (status), and the identifier (id). This distinguishes it from sibling tools zentra_task_create (new task) and zentra_task_list (read tasks).

    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?

    Usage context is implied: the verb 'updates' and 'existing task' indicate this is for modifying an already created task, not for creating or listing. However, no explicit alternatives or exclusionary guidance is given, unlike a tool that names a sibling alternative.

    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 only adds one behavioral note about omitting 'tag', but does not disclose the return format, pagination, read-only nature, potential errors, or any side effects. This is a significant transparency gap for a tool with no annotation support.

    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 two sentences long, front-loaded with the primary action, and contains no redundant or filler wording. Every sentence contributes useful 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?

    With four optional parameters and no output schema or annotations, the description is incomplete. It only mentions two of the four filter parameters (tag and status) and does not describe the output format or behavior beyond the filter logic. This leaves significant context gaps for an agent selecting and invoking 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 description coverage is only 25%, so the description must compensate. It clarifies that 'tag' refers to a project tag and that omitting it returns all projects, and it mentions 'status' as a filter. However, it does not explain 'type' or 'parentId', leaving those parameters without additional semantic context beyond their raw schema definitions.

    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 'Lists tasks from Zentra's production task board' with a specific verb and resource, and mentions optional filters by tag and status. This distinguishes it from sibling tools 'zentra_task_create' and 'zentra_task_move', which are write operations.

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

    Usage Guidelines4/5

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

    Provides clear context: lists tasks from the production board, and explicitly advises omitting 'tag' to see tasks across all projects. It does not explicitly state when not to use it, but the read-only nature of listing is clear from the sibling tool names, making the context sufficient.

    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 this writes to a production board, that tag is required in practice despite being schema-optional, and that any text is accepted for tag. No contradictions with annotations.

    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?

    Three tightly focused sentences: purpose, tag guidance, and type/parent behavior. Every sentence adds value and there is no redundancy or fluff.

    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?

    Given no output schema, the description covers the essential context for a create tool: production target, key parameter behaviors, and type/parent relationships. Minor gaps like return values are acceptable when no output schema exists and the schema fills in most field details.

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

    Parameters4/5

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

    Schema coverage is high (71%), but the description adds meaningful nuance: inferring tag from the working directory, always passing it explicitly, and the parentId hierarchy (BUG/TASK to EPIC, SUBTASK to TASK). This goes beyond the schema's field descriptions.

    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 opens with 'Creates a task on Zentra's production task board' — a specific verb and resource with clear scope. Sibling tools (list, move) are obviously different operations, so the tool is well differentiated.

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

    Usage Guidelines4/5

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

    It gives explicit instructions for the tag parameter ('infer it from your own working directory and always pass it explicitly') and explains type defaults and parentId linking rules. It doesn't name alternatives but the use case is clear from the create vs list/move context.

    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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