Server Quality Checklist

Tool Scores

• add_commentC
  2.9/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool adds a comment but doesn't describe what happens after (e.g., is the comment immediately visible, does it trigger notifications, are there rate limits or authentication requirements?). For a mutation tool with zero annotation coverage, 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 directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place in this minimal but complete statement.

  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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address behavioral aspects like permissions, side effects, or response format, leaving the agent with insufficient context to use the tool effectively beyond basic parameter passing.

  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 both parameters ('issue_id' and 'comment') clearly documented in the schema. The description doesn't add any additional meaning beyond what the schema provides (e.g., format examples or constraints), so it meets the baseline for adequate but unenhanced parameter documentation.

  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 ('Add a comment') and target resource ('to an existing issue in the BLT system'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'submit_issue' or 'update_issue_status' which also involve issue interactions, missing an opportunity for clearer distinction.

  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?

  The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., issue must exist), exclusions, or comparisons to sibling tools like 'submit_issue' (for creating issues) or 'update_issue_status' (for modifying status). This leaves the agent without context for tool selection.

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

• award_baconC
  2.9/5.0
  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. While 'award' implies a write/mutation operation, the description doesn't specify whether this requires special permissions, if points are reversible, what happens if the contributor doesn't exist, or any rate limits. For a mutation tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

  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 concise with two sentences that directly address the tool's purpose. Both sentences earn their place - the first states what the tool does, and the second provides important context about the gamification system. No wasted words or unnecessary elaboration.

  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?

  For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after awarding points (success/failure responses), whether the operation is idempotent, what permissions are required, or how this integrates with the broader system. The context about BLT's gamification system is helpful but doesn't compensate for the missing behavioral information.

  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 all three parameters (contributor_id, points, reason) are documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema, such as format requirements for contributor_id, valid ranges for points, or examples for reason. Baseline 3 is appropriate when the schema does the heavy lifting.

  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 ('award bacon points') and target ('to a contributor'), explaining it's part of a gamification system. However, it doesn't differentiate this tool from its siblings (add_comment, submit_issue, update_issue_status), which all seem to be different types of actions in what appears to be an issue tracking system.

  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?

  The description provides minimal guidance - it only states this is for awarding points in a gamification system. There's no explicit guidance on when to use this tool versus alternatives, nor any mention of prerequisites, constraints, or appropriate contexts for use.

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

• update_issue_statusC
  2.9/5.0
  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 this is an update operation, implying mutation, but doesn't cover critical aspects like required permissions, whether changes are reversible, error handling, or response format. This leaves significant gaps for a mutation tool.

  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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple update tool, though it could be slightly more informative without losing conciseness.

  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 as a mutation operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., side effects, authentication), usage context, and expected outcomes, making it inadequate for safe and effective use by an AI agent.

  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 fully documents all parameters (issue_id, status, comment). The description adds no additional semantic context beyond what's in the schema, such as format details or usage examples, meeting the baseline for high coverage.

  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 ('update') and resource ('status of an existing issue'), specifying the action and target. However, it doesn't differentiate from sibling tools like 'add_comment' or 'submit_issue', which also involve issue operations but for different purposes.

  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?

  The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing issue ID), exclusions, or comparisons to siblings like 'add_comment' for comments without status changes or 'submit_issue' for creating new issues.

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

• submit_issueB
  3.2/5.0
  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. It states this is for submitting new issues, implying a write operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, whether submissions are public or private, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap.

  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 concise sentences with zero waste: the first states the purpose, and the second provides usage context. It's appropriately sized and front-loaded, making it easy to understand quickly.

  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 this is a mutation tool (submitting new issues) with no annotations and no output schema, the description is incomplete. It doesn't cover important aspects like what the tool returns, error conditions, or side effects, which are crucial for an agent to use it correctly in a workflow.

  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 5 parameters thoroughly. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain parameter relationships or usage nuances). Baseline 3 is appropriate when the schema does the heavy lifting.

  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: 'Submit a new issue to the BLT system' with specific examples of what to report ('bugs, vulnerabilities, or other issues'). It distinguishes from siblings like 'add_comment' or 'update_issue_status' by focusing on creation rather than modification, though it doesn't explicitly name these alternatives.

  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 when to use this tool ('to report bugs, vulnerabilities, or other issues'), but it doesn't provide explicit guidance on when not to use it or when to choose alternatives like 'add_comment' for existing issues. The context is clear but lacks exclusion criteria or direct sibling comparisons.

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