Server Quality Checklist

Tool Scores

• authenticate_garminB
  3.1/5.0
  Behavior2/5

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

  With no annotations, the description carries full burden. It discloses that authentication opens a browser, which is useful behavioral context. However, it omits critical details like whether this is a one-time setup, if it stores tokens, error handling, or rate limits. For an auth tool, this is a significant gap in transparency.

  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 a single, efficient sentence that front-loads the core action ('Authenticate with Garmin Connect') and adds a key behavioral detail ('opens browser') without waste. It's appropriately sized for a simple tool with no parameters.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the complexity of authentication (often involving tokens, permissions, or errors) and no annotations or output schema, the description is incomplete. It lacks details on what happens after authentication, success/failure responses, or how it integrates with sibling tools. For an auth tool, this leaves significant 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?

  There are 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add param info, but with no params, a baseline of 4 is appropriate as it doesn't need to compensate for gaps.

  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 ('Authenticate with') and target ('Garmin Connect'), specifying it opens a browser. It distinguishes from siblings like 'check_garmin_auth' (verification) and 'create_garmin_workout' (creation), though it doesn't explicitly contrast them. The purpose is specific but could be more differentiated.

  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 is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing credentials), when authentication is required, or how it relates to sibling tools like 'check_garmin_auth'. The description implies usage for initial auth but lacks explicit context or exclusions.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• check_garmin_authB
  3.1/5.0
  Behavior2/5

  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 states the tool checks authentication validity but doesn't describe what 'valid' means (e.g., token expiration, scope sufficiency), what happens on failure, or any side effects like rate limits or logging. This leaves significant gaps for a tool that likely interacts with external APIs.

  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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's complexity (involving external authentication checks) and lack of annotations and output schema, the description is incomplete. It doesn't explain what constitutes valid authentication, potential error conditions, or return values, leaving the agent with insufficient information for reliable use.

  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 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to add parameter details, and it correctly implies no inputs are required for checking auth status, aligning with the schema.

  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 as checking Garmin authentication validity, using a specific verb ('check') and resource ('Garmin authentication'). However, it doesn't differentiate from sibling tools like 'authenticate_garmin' which might handle initial authentication versus checking existing validity.

  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 is provided on when to use this tool versus alternatives like 'authenticate_garmin' for initial setup or 'create_garmin_workout' for operations requiring valid auth. The description implies usage for checking validity but lacks explicit context or exclusions.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• create_garmin_workoutB
  3.3/5.0
  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. While it mentions the creation action, it doesn't disclose critical behavioral traits such as authentication requirements (implied by sibling tools but not stated), potential side effects (e.g., whether this persists data or requires confirmation), error handling, or rate limits. The description is minimal and lacks necessary operational context.

  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?

  The description is appropriately sized with two sentences that are front-loaded with the main purpose. Every sentence earns its place by stating the tool's function and its role in the workflow, though it could be slightly more structured for clarity.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the complexity of a creation tool with no annotations and no output schema, the description is incomplete. It lacks details on authentication needs (implied by siblings but not stated), behavioral traits, error responses, or what happens post-creation. For a mutation tool, this leaves significant gaps in understanding how to use it effectively.

  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 doesn't add any additional meaning beyond what's in the schema (e.g., it doesn't explain parameter interactions or provide examples not in the schema). Baseline 3 is appropriate as the schema does the heavy lifting, but no extra value is added.

  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 specific action ('Create a workout in Garmin Connect') and resource ('from structured workout data'), distinguishing it from sibling tools like authenticate_garmin and check_garmin_auth. It explicitly mentions the tool's role in the workflow: Claude should parse natural language and pass structured data.

  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 implies usage by stating 'Claude should parse the natural language description and pass structured workout steps,' suggesting this tool is used after natural language processing. However, it doesn't explicitly state when to use this tool versus alternatives or provide exclusions, leaving some ambiguity about its specific context in relation to sibling tools.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.