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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: search, list, get details, get transcript for meetings, and list teams and team members. There is no ambiguity or overlap.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern in snake_case (e.g., search_meetings, list_teams). The minor pluralization difference between 'list_teams' and 'list_team_members' is natural and acceptable.

    Tool Count5/5

    The server has 6 tools, which is well-scoped for a simple meeting and team management server. Each tool serves a necessary function without being redundant or excessive.

    Completeness4/5

    The tool set covers all read operations for meetings (search, list, details, transcript) and teams (list teams, members). However, it lacks any write operations (create, update, delete), which may be intended but is a minor gap for a full lifecycle.

  • Average 4.1/5 across 6 of 6 tools scored. Lowest: 3.2/5.

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

    • No community issues in the last 6 months
    • 6 commits in the last 12 weeks
    • Last stable release on
    • 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

  • Behavior3/5

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

    Annotations already declare readOnlyHint=true, so no contradiction. The description doesn't add behavioral details beyond retrieving data, but it doesn't mislead. Minimal added value over 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?

    Two-line description is concise and includes an example. No unnecessary words, though it could be slightly more informative.

    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?

    The description provides the core purpose and an example. Given the presence of an output schema and only one parameter, it is moderately complete but could elaborate on what the transcript includes (e.g., if it returns the full text or just metadata).

    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%, and the description merely adds an example call without clarifying parameter semantics beyond the schema's description. 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 it retrieves a meeting transcript with essential metadata, using a specific verb and resource. While it doesn't explicitly differentiate from get_meeting_details, the focus on 'transcript' sets it apart from other meeting tools.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    No guidance on when to use this tool versus siblings like get_meeting_details or list_meetings. The example shows syntax but lacks context for selection.

    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 indicate readOnlyHint=true, so the description adds value by disclosing pagination behavior with cursor usage and provides examples, which is sufficient for a read-only list tool.

    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 brief (two sentences plus examples), front-loaded with the core purpose, and every element is useful without redundancy.

    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 list tool with an output schema, the description adequately covers pagination and structure, though it could mention fields returned. The output schema compensates, so overall it's sufficiently complete.

    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?

    The description does not elaborate on parameters beyond schema descriptions, which already cover cursor and per_page. The examples illustrate cursor usage but add minimal new semantic meaning.

    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 uses a specific verb 'Retrieve' and resource 'teams', and the phrase 'paginated list with organizational structure' clearly distinguishes it from sibling tools like list_meetings or list_team_members.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    No guidance on when to use this tool versus alternatives; no mention of prerequisites or when not to use it.

    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 declare readOnlyHint=true, and description aligns with read-only retrieval. Adds value by detailing optional content inclusion (action items, CRM matches) and pagination. No contradiction.

    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?

    Single clear sentence followed by well-structured examples. Every element earns its place, no redundancy.

    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 presence of output schema, description adequately covers pagination, filtering, and optional content. Could mention sorting or ordering but not critical.

    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 examples that illustrate usage but no new semantic information beyond schema. Baseline 3 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 clearly states the tool retrieves paginated meetings with filtering and optional content inclusion. It distinguishes from siblings like search_meetings and get_meeting_details by focusing on pagination and list operation.

    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?

    Examples provide clear usage patterns, but no explicit guidance on when to prefer this over search_meetings or other siblings. Context is clear but lacks exclusions.

    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?

    Description aligns with readOnlyHint annotation, stating 'Retrieve'. Adds context about pagination and filtering but does not disclose other behaviors like rate limits, order, or error handling. Adequate given simple read operation.

    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?

    Description is concise with a single sentence and relevant examples, front-loading purpose. No unnecessary 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?

    For a list tool with output schema, the description covers pagination and filtering. Could mention default per_page value, but overall sufficient. Output schema fills gaps.

    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?

    Despite 0% schema description coverage per context signals, the description provides examples that demonstrate parameter usage. The examples help clarify team and cursor parameters, though per_page default is not mentioned. Partial compensation.

    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 name and description clearly indicate the tool retrieves paginated team members with optional team filtering, distinguishing it from sibling tools like list_teams which list teams, not members.

    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?

    Examples show when to use the tool: default all members, filter by team, paginate. Usage is implied, but no explicit guidance on when not to use or alternatives. Clear enough for most cases.

    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 indicate readOnlyHint=true. Description adds useful context: returns summary, metadata, and explicitly states (without transcript). No contradictions.

    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 plus example. Front-loaded with purpose. No redundant information. Highly efficient.

    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?

    With output schema existing, description adequately covers what the tool returns (summary, metadata, no transcript) and example. No gaps for a simple single-parameter read 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%. Description adds an example call showing the parameter but does not provide additional meaning beyond what the schema describes.

    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?

    Clearly states it retrieves comprehensive meeting details including summary and metadata, explicitly excluding transcript. Differentiates from get_meeting_transcript which would provide transcript. Includes example call.

    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?

    Implicitly guides when to use: when summary/metadata needed, not transcript. Lacks explicit 'when not to use' or direct sibling comparison, but the exclusion of transcript is clear enough.

    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 discloses fuzzy matching, case-insensitivity, pagination, default transcript exclusion, and read-only nature, adding significant value beyond the readOnlyHint annotation.

    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?

    Every sentence serves a purpose; the description is well-structured with clear explanations and practical examples, front-loading key info.

    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 (2 params, output schema exists), the description covers search behavior, fuzzy matching, performance trade-off, pagination, and provides examples, making it fully self-contained.

    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 both parameters with descriptions. The description adds examples and clarifies the query scope (titles, participants, etc.) and default behavior of include_transcript, enhancing understanding.

    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 identifies the tool as searching meetings by keyword across metadata and optionally transcripts, distinguishing it from sibling tools like list_meetings and get_meeting_details.

    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 clear context on when to use metadata-only vs transcript-inclusive searches, notes performance trade-offs, and gives examples. Lacks explicit when-not-to-use guidance but is sufficient.

    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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