Server Quality Checklist

Tool Scores

• linkedin_auth_statusA
  3.7/5.0
  Behavior2/5

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

  No annotations are present, so the description must disclose behavioral traits. It only states the function and lacks details on whether the check is read-only, whether it makes network calls, or what the return value looks like. This is insufficient for a tool with 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?

  The description is a single concise sentence, front-loaded with the verb 'Check' and clear about the resource. No wasted words.

  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 tool is simple, but the description doesn't specify the return format or how to interpret the status (e.g., boolean vs. object), which would help an agent decide next steps. Adequate but has a clear gap.

  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 zero parameters, and the schema provides full coverage. The description adds no parameter details, but none are needed. Baseline 4 is appropriate for zero-parameter tools.

  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's function: checking LinkedIn OAuth completion and local token availability. This distinguishes it from siblings like linkedin_authenticate (initiating auth) and profile/post tools.

  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 intended use is implied as a precondition check before other LinkedIn operations, but no explicit guidance or alternatives are provided. It does not suggest using linkedin_authenticate if auth is missing, though the context makes this inferable.

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

• linkedin_create_postA
  3.7/5.0
  Behavior2/5

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

  No annotations are provided, so the description must convey behavioral implications. It states 'Publish' which indicates a mutating action, but does not disclose that the post becomes public, that the action is irreversible, or that there may be rate limits or permissions required. The confirm parameter hints at deliberate action, but the description itself adds no such 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 a single clear sentence that is front-loaded with the action and resource. Every word earns its place, and there is no redundancy or filler.

  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 simplicity of the tool (two parameters, no output schema), the description covers the basic purpose. However, it lacks critical behavioral context such as irreversibility and public visibility, and it does not mention what the tool returns on success or failure. The schema covers parameters but not these operational aspects.

  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 parameters are already well-documented in the schema. The description adds no additional semantic meaning beyond what 'commentary' and 'confirm' already convey. Baseline of 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 uses the specific verb 'Publish' and clearly identifies the resource as 'a text post to the authenticated member's LinkedIn profile.' It distinguishes itself from sibling tools which are about authentication and profile retrieval.

  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 clearly implies the tool is for posting text content to LinkedIn. It does not explicitly state when not to use it or mention alternatives, but among siblings it is the only posting tool, making the usage context clear enough.

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

• linkedin_get_my_profileA
  4.2/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden. It explicitly states 'Read', indicating a safe, non-destructive operation, and notes the data scope (OpenID profile and email). It adds context about authentication but does not detail response structure or error behavior, which would have raised it higher.

  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, concise sentence of 10 words. It front-loads the action and resource without any wasted words or redundant detail, making it an exemplary concise description.

  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 tool's simplicity (0 parameters, no output schema, no annotations), the description provides sufficient context: it names the resource, indicates authentication, and hints at return content. It lacks details on response format, but for a standard OpenID profile read, this is adequate.

  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 input schema is empty with zero parameters, so there is nothing to explain. The baseline for 0 parameters is 4; the description adds no parameter-related information because none exists, which 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 clearly states the action ('Read') and the specific resource (the authenticated LinkedIn member's OpenID profile and email). This distinguishes it from siblings like 'linkedin_auth_status' (checking auth status) and 'linkedin_create_post' (creating content), making the purpose unambiguous.

  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 the tool is used to retrieve profile/email data for the authenticated user, but it does not explicitly mention when not to use it or point to alternatives like 'linkedin_auth_status' for status checks. The usage is inferable but not explicitly framed.

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

• linkedin_authenticateA
  4.6/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden of disclosure. It explains that the tool returns a URL requiring browser interaction and that authentication is not complete until linkedin_auth_status is called. This is valuable behavioral context beyond what any structured field provides.

  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 two sentences, front-loaded with the purpose and followed by concise step-by-step guidance. Every word earns its place, with no redundancy or fluff.

  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 zero-parameter tool initiating a simple two-step OAuth flow, the description covers the essential workflow: initiating the sign-in, handling the returned URL, and proceeding to the status check. It could specify the response shape or error cases, but it is complete enough for an agent to act successfully.

  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 zero parameters, so there is no schema to explain. A baseline of 4 is appropriate given that the description does not need to compensate for missing parameter documentation.

  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 'Start LinkedIn OAuth sign-in' with a specific verb and resource, unambiguously identifying the tool's function. It distinguishes itself from siblings like linkedin_auth_status (which checks status) and linkedin_get_my_profile (which fetches profile data).

  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 sequential instructions: open the returned URL, approve access, then call linkedin_auth_status. It names the next tool, effectively giving an alternative/next step and clarifying when to use this tool versus the status tool.

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