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Server Quality Checklist

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  • Latest release: v1.0.1

  • Disambiguation5/5

    Each tool maps to a distinct Taiga resource: projects, work items, sprints, comments, attachments, and wiki. Shared type/item parameters are used for child resources, but the tool purposes do not overlap.

    Naming Consistency4/5

    Top-level tool names are simple lowercase resource nouns and are internally consistent. The pattern is slightly mixed because some names are plural resources while work and wiki are singular, and the internal op verbs vary between add/create and edit/update.

    Tool Count5/5

    Six resource-scoped tools is a well-balanced surface for a project-management server. Each tool represents a meaningful functional area without making the tool list overwhelming.

    Completeness4/5

    The server covers most core workflows: project inspection, work-item CRUD, sprints, comments, attachments, and wiki with lifecycle operations. Deliberate gaps such as project creation/deletion and sprint update/delete prevent it from being fully complete.

  • Average 4.6/5 across 6 of 6 tools scored.

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

    • No community issues in the last 6 months
    • 10 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 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

  • Behavior4/5

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

    The description adds helpful behavioral details beyond the annotations: download writes files to savePath when provided, and upload resolves local:// URIs through the harness. The destructiveHint annotation is consistent with the delete operation, and no annotation contradiction exists.

    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 compact, well organized, and front-loads the core purpose in one clause. The table conveys a large amount of operation-parameter information without unnecessary prose, and every line adds utility.

    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?

    The tool has many parameters and a multi-operation structure, but the operation table plus schema descriptions cover the calling requirements well. It could offer more on return shapes, permissions, or side effects, though it remains sufficient for reliable invocation.

    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 of 100 percent means baseline is 3, but the description still adds meaningful value through a required/optional argument matrix per operation. It clarifies the relationship between operation and parameter choice, especially the 'filePath OR fileContent' upload requirement.

    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 a precise verb set — 'List, upload, download, or delete attachments' — and scopes it to 'work items and wiki pages.' The operation table further disambiguates each action, and the tool name plus resource clearly separates it from sibling tools like comments and wiki.

    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?

    The table gives clear operational context by mapping each op to required and optional arguments. It implicitly tells the agent when to use an operation but does not explicitly discuss exclusions or mention specific sibling alternatives for choosing between tools.

    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?

    Annotations already declare readOnly/idempotent/openWorld hints. The description adds behavioral context: credentials are sourced from environment variables and authentication occurs on first use. This explains the tool's interaction with external state without contradicting the 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?

    The description is compact and well-structured, using a table to organize the three operations. No redundant sentences; all content is informative.

    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 no output schema, the description briefly indicates return types (e.g., 'list projects', 'inspect metadata, owner, member count', 'show current user info'), which is sufficient for a read-only tool. It covers credential handling and operation-specific arguments effectively.

    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?

    The input schema already describes op and project (100% coverage). The description goes further by mapping each operation to its required/optional arguments, clarifying that get needs project while list and whoami don't, which is not evident from the schema alone.

    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 explicitly states 'List or inspect Taiga projects and verify credentials' and then enumerates three operations (list, get, whoami) in a structured table, making the tool's purpose unmistakable and distinct from siblings like sprints or work.

    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 explicit guidance to use the whoami operation for credential verification, and the table indicates when each op applies (e.g., get for inspecting a specific project's metadata). While it doesn't name sibling alternatives, the resource-specific scope makes the use case clear.

    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?

    The description explicitly warns that delete is permanent and that Taiga has no trash, and explains the batch create-only safeguard prevents accidental board clearing. This adds substantial safety context beyond the destructiveHint annotation, and there is no contradiction 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?

    The description is compact and well-structured, starting with a one-line summary followed by a bulleted list of operations. Every sentence provides operational guidance, with no filler or redundant information.

    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?

    All seven operations have their required parameters stated, the delete behavior carries a detailed permanence warning with rationale, and the batch limit is explicitly noted. Without an output schema, this description sufficiently covers invocation semantics for a complex 21-parameter 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 100%, so all 21 parameters already have descriptions. The tool description only reiterates which parameters are required for specific operations (e.g., project required) without adding new semantic meaning. The schema carries the parameter documentation burden.

    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 states 'Manage Taiga work items (issues, user stories, tasks, epics)' and enumerates seven distinct operations with specific verbs (list, get, create, update, link, unlink, delete). This makes the tool's purpose unambiguous and clearly distinguishes it from sibling tools like projects, sprints, and wiki.

    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?

    The operation list provides clear context with required parameters for each operation (e.g., 'project required', 'item required') and includes a safety warning about delete being permanent. However, it does not explicitly state when to use this tool over alternatives, though the separation from siblings is implicit in the description.

    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?

    The description exposes meaningful behavior beyond the annotations: delete is described as permanent, update is described as OCC versioned, watch defaults to true, and list/get inspect metadata and content. This goes well beyond the bare readOnlyHint=false and destructiveHint=true annotations.

    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 operation table is a compact and scannable way to present six different modes in one tool. It is mainly efficient, although the repeated 'project needed if page is slug' note could be consolidated; still, the structure gives high clarity without unnecessary prose.

    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?

    The description is highly complete for selecting and invoking each operation because it maps required args, slugs, content format, watch default, and destructive flag. With no output schema, a little more detail about the actual returned data shape would round it out, but the agent can safely and correctly call the tool.

    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?

    The table adds per-operation required/optional semantics beyond the raw schema, clarifies page as ID/slug, and explains when project is needed. It also documents content as Markdown and watch default behavior, so an agent can invoke each operation correctly without guessing parameter combinations.

    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 begins with a clear action list—'Create, inspect, update, delete, or watch wiki pages'—and then concretely defines each operation against the wiki page resource. This makes the tool's scope unambiguous and keeps the list/get/create/update/delete/watch overloaded operation distinct from sibling resource tools.

    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?

    The operation table gives explicit routing for each op and states which arguments are required versus optional, including the important condition that project is needed when page is a slug. It does not explicitly contrast the tool with sibling tools, but the table provides sufficient when-to-use guidance for each operation.

    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?

    Beyond the annotations, the description reveals a key behavioral nuance: 'Taiga soft-deletes comments on delete'. This explains how deletes behave and makes the includeDeleted parameter meaningful. It also implies deletion might be reversible, which adds context not available from the annotations alone.

    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 introductory sentence followed by a compact, readable table. Every piece of content in the table contributes to understanding operation-specific argument requirements, with no fluff or repetition of schema details. The purpose is front-loaded in the first clause.

    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 (7 params, no output schema, 4 operations), the description provides a complete operation-by-operation breakdown of required and optional arguments. The soft-delete note and the includeDeleted parameter are explained in a way that leaves nothing ambiguous.

    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?

    The schema already covers all parameter descriptions (100% coverage), so the baseline is 3. The description's operation matrix adds value by showing which parameters are conditionally required for each 'op' (e.g., commentId only for edit/delete, text only for add/edit), which the schema does not convey. This extra relational information raises the score above 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 opens with a clear verb phrase ('List, add, edit, or delete') and names the exact resource types (issues, user stories, tasks, epics, wiki pages). It unambiguously identifies this tool as the comment-handling tool, separating it from siblings like 'attachments' and 'wiki'.

    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?

    The operation table gives explicit guidance on which arguments are required for each operation (list vs. add vs. edit vs. delete), helping an agent assemble calls correctly. It lacks an explicit statement of when not to use this tool, but the operations are self-explanatory and no true alternative exists among the listed siblings.

    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?

    Annotations indicate non-read-only, non-destructive, open-world. The description adds valuable context that sprint deletion is intentionally not exposed because it detaches all stories/tasks, a board-wide edit better done in the UI. This goes beyond annotations by explaining the design rationale, though it does not detail auth or rate limits.

    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 well-structured with a brief overview and bullet-pointed operations. Every line provides necessary information without redundancy or fluff.

    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?

    Despite no output schema, the description covers all operations, required parameters, exclusions (deletion), and points to the correct sibling tool for related actions. It is sufficiently complete for an agent to select and invoke the tool.

    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 covers 100% of parameters with descriptions. The description adds operational context (e.g., which parameters are required for which op, project needed when sprint is a name) beyond the schema, improving the agent's ability to invoke the tool correctly.

    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 it manages Taiga sprints with specific operations (list, get, create, stats). It distinguishes from siblings by explicitly mentioning the work tool for deletion and implying project tool for project-level tasks.

    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 operation-specific prerequisites (e.g., 'Requires project' for list, 'project required if sprint is a name' for get/stats). Also gives an alternative: 'Delete individual work items with the work tool instead' when discussing deletion.

    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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