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4regab

tasksync-mcp

by 4regab
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Hybrid

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools serve entirely distinct purposes: get_feedback handles a continuous feedback loop for task management and user interaction, while view_media reads and encodes image files. There is no functional overlap or ambiguity between them, making tool selection clear and straightforward.

    Naming Consistency4/5

    Both tools follow a verb_noun pattern (get_feedback, view_media), which is consistent and predictable. The naming is clear and descriptive, with only a minor deviation in that 'get' and 'view' are slightly different verbs, but they remain semantically appropriate and maintain overall coherence.

    Tool Count2/5

    With only two tools, the server feels under-scoped for its implied domain of task synchronization and media handling. The get_feedback tool is heavily emphasized with extensive mandatory usage rules, suggesting a core focus, but the lack of complementary tools (e.g., for creating, updating, or managing tasks or feedback) makes the set appear incomplete and limited in functionality.

    Completeness2/5

    The server has significant gaps in coverage. While get_feedback provides a feedback mechanism and view_media handles image reading, there are no tools for core task management operations (e.g., create_task, list_tasks, update_task) or broader media manipulation. This incomplete surface will likely hinder agents in performing comprehensive workflows within the domain.

  • Average 4.2/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 0 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

  • Behavior4/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the tool automatically creates an empty feedback.md file if it doesn't exist, it's meant for continuous feedback loops during processes, and it requires repeated calls until explicit termination. However, it doesn't mention potential error conditions, rate limits, or authentication needs, which would be helpful for a tool with such mandatory usage rules.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness2/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is excessively long and repetitive, with the mandatory usage rules section containing redundant information (e.g., multiple rules about continuous calling and termination). The core purpose is buried in verbose directives. While structured, it's not appropriately sized - many sentences don't earn their place through unique information value.

    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 the tool's complexity (mandatory continuous usage pattern) and lack of annotations/output schema, the description provides substantial contextual information about the tool's role in feedback loops, termination conditions, and behavioral expectations. It explains the tool's integration into workflows comprehensively. However, it doesn't describe what the tool returns or how to interpret feedback content, which would be valuable given the lack of output schema.

    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 the schema already documents all three parameters (head, path, tail) with their descriptions. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions the default path ('defaults to ./feedback.md') which is already covered in the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

    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 purpose: 'Read the contents of a feedback.md file' and mentions default behavior (defaults to ./feedback.md). It specifies the verb ('Read') and resource ('feedback.md file'), making the purpose understandable. However, it doesn't explicitly differentiate from the sibling tool 'view_media' beyond the different file type focus.

    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?

    The description provides extensive, explicit usage guidelines through the 'MANDATORY USAGE RULES - PRIMARY DIRECTIVE' section. It details when to use the tool (continuously during processes), when not to use it (only when user explicitly indicates termination), and includes termination conditions. The guidelines are comprehensive and leave no ambiguity about usage context.

    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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it's a read operation (implied by 'Read'), returns base64-encoded data and MIME type, has directory restrictions, streams files efficiently, and supports specific image formats. However, it doesn't mention error handling or performance characteristics.

    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 clear sections (SUPPORTED FORMATS, USAGE, Args), front-loaded with the core purpose, and every sentence adds value without redundancy. It's appropriately sized for the tool's complexity.

    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 the tool's moderate complexity (1 parameter, no annotations, no output schema), the description is largely complete: it covers purpose, usage, parameters, formats, and behavioral traits. However, without an output schema, it could benefit from more detail on return values (e.g., structure of the base64 data).

    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 schema description coverage is 0%, so the description must fully compensate. It provides comprehensive parameter semantics: explains that 'path' is an 'Absolute or relative path to the image file within allowed directories,' clarifying the parameter's purpose and constraints beyond the basic schema type.

    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's purpose with specific verbs ('Read an image file') and resources ('image file'), distinguishing it from the sibling tool 'get_feedback' by focusing on file reading rather than feedback retrieval. It specifies the exact action and resource type.

    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 description provides clear context on when to use this tool ('to read and encode image files for analysis, display, or processing'), but does not explicitly mention when not to use it or compare it to alternatives. The 'Only works within allowed directories' constraint offers some usage boundaries.

    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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