Server Quality Checklist

Tool Scores

• generate_worklogA
  3.5/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It does disclose key behavioral traits: AI enhancement is enabled by default and can be disabled, and it lists accepted date formats. It does not state whether the operation is read-only, whether it makes network calls, or that it does not post the worklog to Povio (a notable distinction given sibling tools). This leaves gaps in the agent's understanding of side effects and workflow.

  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 well-structured: a clear purpose sentence, then AI behavior, then date formats, then examples. It front-loads the core purpose. While the trigger examples are somewhat repetitive (many variations of the same 'wl' / 'generate worklog' phrasing), the overall layout is easy to scan and not excessively verbose.

  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 has no output schema and no annotations, so the description must compensate. It covers the main functionality and inputs, but misses several contextual elements: it does not describe the return format/type, does not clarify default repository behavior (even though the schema mentions 'defaults to current directory'), and does not explain how this tool fits into the larger workflow (e.g., that after generating, you'd use post_worklog to submit). For an AI agent, these are meaningful 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?

  Schema coverage is 100%, so the baseline is 3. The description adds value beyond the schema by expanding on date formats (e.g., '10/28/2024' (MM/dd/YYYY) and '28.10.2024' (dd.MM.YYYY) are not in the schema description) and by providing concrete trigger examples. This extra detail helps the agent construct valid inputs.

  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 opens with a clear specific verb+resource: 'Generate a worklog from git commits.' It explains the process (analyzes commit messages, extracts ticket numbers, creates AI-enhanced descriptions). However, it does not explicitly differentiate itself from sibling tools like 'post_worklog' or 'generate_and_post_worklog' – it never says 'this only generates, does not post' – so it lacks explicit sibling distinction.

  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?

  Usage context is implied through trigger examples ('wl', 'generate worklog', 'what did I work on yesterday') and supported date formats, which tells the agent when a user request maps to this tool. However, there is no explicit when-to-use vs. alternatives guidance, such as 'use post_worklog to submit' or 'use generate_and_post_worklog to both generate and post.' The examples are helpful but not selection-oriented.

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

• post_worklogA
  3.6/5.0
  Behavior3/5

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

  With no annotations provided, the description carries full transparency burden. It discloses important behavior: supports both project ID and name, and falls back to DEFAULT_PROJECT_ID from the environment. However, it does not reveal return format, error handling, or side effects beyond the expected posting action. The added context goes beyond a tautology but remains incomplete for a mutation without 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?

  The description is front-loaded with a clear purpose sentence followed by a concise summary of identifier resolution. The list of trigger examples is helpful but somewhat repetitive, with nearly a dozen examples that could be trimmed. Still, the structure is clean and the core message is efficient, so it earns a 4 rather than a 5.

  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 has three required params, no output schema, and no annotations. The description compensates by explaining default project behavior and providing usage examples, which cover invocation scenarios. However, it omits what the tool returns on success or failure, and does not mention validation rules beyond the schema. Given the simplicity of the operation, this is adequate but not comprehensive.

  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%, so all five parameters are described in the input schema. The description's mention of projectId/projectName alternative and DEFAULT_PROJECT_ID is already present in the schema descriptions. Thus the description adds no meaningful parameter semantics beyond the schema, justifying the baseline score of 3.

  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 opens with 'Post a worklog entry to Povio dashboard', a specific verb+resource statement that clearly defines the tool's function. It distinguishes from siblings by explicitly focusing on posting, while also noting support for both project ID and name. This is unambiguous and differentiates from 'list_povio_projects' and 'generate_worklog'.

  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 trigger examples provide useful input patterns for how the tool might be invoked, but the description does not explicitly state when to prefer this tool over alternatives like generate_and_post_worklog. It neither specifies exclusions nor mentions the sibling tools, leaving the agent to infer usage context. The examples are a form of guidance, but they lack comparison to alternatives.

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

• generate_and_post_worklogA
  4.3/5.0
  Behavior4/5

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

  With no annotations, the description carries the transparency burden. It discloses that AI enhancement is enabled by default and pauses posting for AI to create an enhanced description, and that setting enhanceWithAI to false disables this (not recommended). This adds valuable behavioral context beyond the schema.

  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 well-organized with a clear purpose sentence first, followed by date formats and trigger examples. It is longer than necessary but every section serves a purpose, and the structure aids readability.

  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 combined generation+posting tool with no output schema, the description covers key behavioral aspects: the AI pause, project resolution, and date formats. It does not describe return values or error cases, but these are less critical for a one-step action tool.

  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?

  While schema coverage is 100%, the description adds practical semantics: explains supported date formats, clarifies that enhanceWithAI defaults to enabled, and that projectName will be resolved automatically. These details go beyond the bare schema descriptions.

  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 combined function: 'Generate worklog from git commits AND post it to Povio in one step.' It explicitly distinguishes from siblings by the 'one step' fusion of generation and posting, and mentions support for both project ID and name.

  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 clear context and trigger examples for when to use the tool, such as 'wl FaceFlip 8' or 'generate and post worklog for today with 8 hours.' However, it does not explicitly state when to prefer the individual siblings (generate_worklog or post_worklog) over this combined tool.

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

• list_povio_projectsA
  4.5/5.0
  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 reveals key behavioral scoping: only 'active' projects and only projects 'assigned to you.' It also states the output format (names and IDs). For a read-only list operation, this is sufficient transparency, though it doesn't mention error handling or authentication requirements.

  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 concise and front-loaded: the first sentence states the core purpose, the second sentence provides trigger examples that aid an AI agent in recognizing when to invoke the tool. Every sentence earns its place; there is no fluff.

  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?

  For a simple list tool with no parameters and no output schema, the description is complete. It states what it does, what it returns, and the scope of data (active, assigned to you). No additional details are necessary for an agent to correctly select and invoke the tool.

  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 the schema already covers everything. The description adds context about what is listed (active, assigned to you) but doesn't need to explain parameter syntax. Baseline 4 is appropriate for 0-param 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 a specific verb and resource: 'List all active projects assigned to you in Povio.' It also specifies the output (project names and IDs) and how it's useful (for posting worklogs), which distinguishes it from sibling tools that post worklogs.

  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 clear context for when to use the tool, including trigger examples like 'wl list' and 'list my povio projects.' It explicitly ties usage to posting worklogs, but does not explicitly state when not to use it or name alternatives. The sibling tools are worklog-related, so the implied distinction is strong.

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