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no39pikko

LeadClaw MCP

by no39pikko
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Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool serves a distinct purpose: booking appointments, checking status, and retrieving details. There is no ambiguity between them.

    Naming Consistency5/5

    All tools follow the verb_noun pattern with snake_case (book_appointments, check_status, get_appointment_details), providing a predictable naming scheme.

    Tool Count4/5

    Three tools is slightly minimal for the domain but covers the core workflow of booking, tracking, and reviewing appointments. It is reasonable for the service's scope.

    Completeness4/5

    The tool set covers the primary lifecycle (book, monitor, view details). Minor gaps like cancellation or rescheduling exist but are not critical for the stated purpose.

  • Average 4.1/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 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

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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 full burden. It transparently states the return values (current phase and confirmed appointments) and polling nature. No side effects or constraints are mentioned, but for a read operation it is adequate.

    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 with no wasted words. Information is front-loaded and every sentence serves a purpose.

    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 simplicity of the tool (one param, no output schema), the description adequately explains return values and usage. Could be slightly more detailed on error states, but overall complete for a polling 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 coverage is 100% with one parameter fully described. The description adds usage context (calling after book_appointments) but does not add new semantic meaning beyond the schema, so baseline score of 3 is appropriate.

    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 verb 'check' and the resource 'progress of a LeadClaw appointment request', listing return values. While it distinguishes from book_appointments, it does not explicitly differentiate from sibling get_appointment_details, though the purpose is specific enough.

    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 explicit usage context: 'Call this after book_appointments and re-poll as needed until status is completed.' It gives clear when-to-use but lacks when-not-to-use or alternatives for get_appointment_details.

    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?

    No annotations provided. The description conveys it is a read operation fetching details of a confirmed appointment, but does not disclose additional traits like permissions, side effects, or error scenarios. It adds value over no description but lacks depth.

    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, front-loaded with capability, no filler. Second sentence provides usage guidance. Every sentence adds 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?

    For a simple tool with one parameter and no output schema, the description lists the returned data and usage context. It is adequate, though it could mention error cases or confirm the appointment must be 'confirmed'.

    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 a good description for appointment_id. The tool description adds minimal extra meaning, reinforcing the parameter's source. Baseline 3 is appropriate.

    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 'Pull full briefing on a specific confirmed appointment' and lists the data returned (contact info, BANT, etc.). It clearly distinguishes from siblings 'book_appointments' and 'check_status'.

    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 says 'Use when the user wants to prep for a specific meeting,' which is a clear when-to-use. It does not explicitly mention alternatives, but the sibling context provides that.

    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 provided, so description carries full burden. Discloses human SDRs handle outbound, pay-per-meeting model, BANT qualification, and returns request_id. Lacks timing details.

    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 sentences front-loaded with core function, business model, and usage guidance. No superfluous words.

    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?

    Covers workflow, return value, and sibling tool link. No output schema, but explanation of polling suffices. Minor gaps on error handling.

    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 coverage is 100% with all parameters described. Description adds high-level context but no additional detail beyond schema, meeting 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 clearly states it requests confirmed sales appointments, differentiating it from siblings check_status and get_appointment_details by explicitly mentioning polling for results.

    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 says when to use: when user wants meetings but not outreach; implies alternatives (do outreach yourself). Also directs to poll check_status.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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