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khughitt

Polybar Notification MCP

by khughitt
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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation2/5

    The two tools have overlapping purposes—both are described as 'useful for notifying the user when an operation is complete or when waiting for user input.' This creates ambiguity, as an agent might struggle to choose between displaying a message in the polybar status bar versus showing a popup notification, since their use cases are not clearly differentiated. The descriptions do not specify distinct scenarios or advantages for each tool, leading to potential misselection.

    Naming Consistency5/5

    The tool names follow a consistent verb_noun pattern with clear, descriptive terms: 'display_polybar_message' and 'show_popup_notification.' Both use snake_case and start with action verbs ('display' and 'show'), making them predictable and easy to understand. There are no deviations in naming conventions, ensuring readability and coherence.

    Tool Count2/5

    With only 2 tools, the server feels thin for a notification domain that could benefit from more granular operations, such as different notification types, priorities, or durations. While the count is minimal, it may be too few to cover common notification workflows effectively, limiting the server's utility and causing agents to work around gaps in functionality.

    Completeness2/5

    Inferring the domain as user notifications, the tool set is severely incomplete. It lacks operations for managing notifications (e.g., dismissing, updating, or clearing notifications), handling different notification styles or priorities, or integrating with other notification systems. This creates significant gaps that could lead to agent failures when trying to perform common notification-related tasks beyond basic display.

  • Average 3.5/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 11 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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool uses 'notify-send/dunst' which implies system-level notification behavior, but it doesn't disclose critical traits like whether it requires specific permissions, if it's synchronous/asynchronous, error handling, or platform dependencies. For a tool with no annotation coverage, this leaves significant gaps in understanding its operational behavior.

    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 extremely concise and well-structured: two sentences that directly state the tool's purpose and usage context. Every word earns its place with no redundancy or fluff. It's front-loaded with the core functionality and follows with practical guidance.

    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?

    Given the tool's moderate complexity (5 parameters, no output schema, no annotations), the description provides basic completeness but has gaps. It covers what the tool does and when to use it at a high level, but lacks details on behavioral traits, error conditions, or integration with the sibling tool. Without annotations or output schema, more context would be helpful for full understanding.

    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%, with all 5 parameters well-documented in the schema (e.g., 'message' as notification content, 'urgency' with enum values). The description adds no parameter-specific information beyond what's in the schema. According to the rules, with high schema coverage (>80%), the baseline is 3 even with no param info in the description.

    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: 'Show a popup notification using notify-send/dunst.' It specifies the verb ('show'), resource ('popup notification'), and implementation method. However, it doesn't explicitly differentiate from its sibling tool 'display_polybar_message' beyond mentioning 'popup' vs. 'polybar' in names, leaving some ambiguity about when to choose one over the other.

    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 description provides implied usage guidance: 'Useful for notifying the user when an operation is complete or when waiting for user input.' This gives context on when to use it, but it doesn't explicitly state when NOT to use it or mention the sibling tool as an alternative. The guidance is helpful but lacks explicit exclusions or comparisons.

    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?

    With no annotations provided, the description carries the full burden. It describes the tool's purpose and use cases but lacks details on behavioral traits such as permissions needed, error handling, or whether it's read-only or destructive. The description doesn't contradict annotations (none exist), but it's minimal on behavioral context.

    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 appropriately sized with two concise sentences that directly state the tool's function and its usefulness. It's front-loaded with the core purpose and avoids unnecessary details, making it efficient and easy to understand.

    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?

    Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers purpose and usage but lacks details on behavioral aspects like return values or error conditions. With no output schema, it should ideally mention what happens after display, but it's minimally viable.

    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 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as explaining parameter interactions or edge cases. This meets the baseline of 3 when schema coverage is high.

    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 action ('Display a message') and target ('in polybar status bar'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from the sibling tool 'show_popup_notification' beyond mentioning polybar specifically, which is good but not fully comparative.

    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 for when to use this tool ('Useful for notifying the user when an operation is complete or when waiting for user input'), giving practical scenarios. It doesn't explicitly state when not to use it or name alternatives like the sibling tool, but the context is sufficient for informed usage.

    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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