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mohitbadwal

Ringback

by mohitbadwal
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Python
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Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: alert_me sends real alerts, alert_status checks configuration, and alert_test sends a test notification. There is no overlap or ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (alert_me, alert_status, alert_test) with underscores, making them predictable and easy to understand.

    Tool Count5/5

    With only 3 tools, the server is well-scoped for its purpose of sending alerts and checking status. Each tool earns its place, and the count is within the ideal 3-15 range.

    Completeness4/5

    The server covers the core operations: sending alerts, checking configuration, and testing connectivity. While missing features like alert history or cancellation, it provides a complete surface for its stated purpose.

  • Average 4.8/5 across 3 of 3 tools scored.

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

    • 0 of 1 community issues answered or closed in the last 6 months
    • 42 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 Apache 2.0.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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, the description carries the full burden. It discloses that 'no secrets revealed', indicating privacy behavior, and lists the specific information shown. It doesn't detail permissions or side effects, but as a read-only report, that's acceptable.

    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?

    Two concise sentences, front-loaded with the core purpose. Every word adds value, and no extraneous 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?

    Given zero parameters and an existing output schema, the description sufficiently covers the tool's function and output details (channels, credentials, rate limits). It is complete for its simplicity.

    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 tool has no parameters, so the baseline is 4. The description does not need to explain parameters, and it adds context about what the output contains.

    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 reports which alert channels are configured, and specifies details like active channel, credentials status, and rate-limit settings. This distinct purpose differentiates it from sibling tools alert_me and alert_test.

    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 explicitly says 'Useful for debugging setup', giving clear context for when to use the tool. However, it doesn't mention alternatives or when not to use it, but the zero-parameter nature makes it straightforward.

    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?

    Discloses key behavioral trait: always uses 'info' severity, so it won't fire loud or repeating critical alerts. This is crucial despite no 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?

    Two sentences, concise and front-loaded with purpose. Every sentence adds value with zero waste.

    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?

    Fully complete for a 0-parameter tool with output schema. Covers purpose, usage, and safety considerations adequately.

    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?

    No parameters exist, so schema coverage is trivial. Description correctly omits parameter details as none are needed.

    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 sends a low-priority TEST notification to verify connectivity. It distinguishes itself from siblings by specifying it's for testing, not for real conditions.

    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?

    Explicitly states when to use: during setup to confirm phone receives pushes, and when not to: rely on alert_me for real conditions.

    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?

    Despite having no annotations, the description fully discloses behavioral traits: it interrupts the user in the real world, the severity parameter alters intrusiveness (including a potential phone call for critical), and it returns a status string. This level of detail compensates for the lack of 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 efficiently structured: a core sentence, then usage guidelines in bullet-style lists, then parameter details. Every sentence adds value, no filler. The front-loading of the key verb and impact ensures the agent quickly grasps the purpose.

    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 (multiple severity levels, real-world interruption, return value), the description covers all necessary aspects: purpose, usage guidelines, parameter meanings, and return type. The mention of a phone call for 'critical' severity is a critical behavioral detail. With an output schema present, the description is fully adequate for an agent to use this tool correctly.

    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 input schema has 0% description coverage, but the 'Args' section in the description adds rich semantic details for each parameter. For example, 'message' is described as a one-sentence lock-screen body with specificity requirements, and 'severity' outlines the exact behavior for each level, far exceeding the schema's type-only information.

    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 starts with a specific verb 'buzz', a clear target 'user's phone', and an effect 'urgent push notification', immediately establishing the tool's core action. It further clarifies that this is a real-world interruption, which differentiates it from typical informational outputs.

    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 explicit 'USE FOR' and 'DO NOT USE FOR' sections, offering clear guidance on when the tool is appropriate and when it is not. It suggests alternatives for non-urgent messages ('belong in the normal reply'), effectively helping the agent make correct decisions.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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