Server Quality Checklist

Tool Scores

• grok_codeB
  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. It mentions 'Returns assistant text by default,' which hints at output behavior, but doesn't disclose critical traits like whether this is a read-only or mutating operation, authentication needs, rate limits, error handling, or what 'raw_output' and 'timeout_s' parameters imply. For a tool with 6 parameters and no annotations, this is insufficient.

  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 and front-loaded, with the core purpose stated first. Both sentences add value: the first defines the tool's function, and the second clarifies parameters and output. There's no wasted text, making it efficient.

  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 tool's complexity (6 parameters, no annotations, but with an output schema), the description is moderately complete. It covers the basic purpose and hints at some parameters, but since there's an output schema, it doesn't need to detail return values. However, the lack of behavioral disclosure and incomplete parameter semantics make it inadequate for full understanding.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description must compensate. It mentions 'language hint and context (e.g., file snippets or requirements),' which adds meaning for 'language' and 'context' parameters, but doesn't explain 'task,' 'model,' 'raw_output,' or 'timeout_s.' With 6 parameters, this partial coverage leaves significant gaps in understanding.

  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: 'Ask Grok for code or code-related guidance.' It specifies the verb ('Ask Grok') and resource ('code or code-related guidance'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like grok_chat or grok_query, which likely handle different types of queries.

  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 provides some implied usage context by mentioning 'code or code-related guidance' and suggesting parameters like language hint and context. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., grok_chat for general chat, grok_query for non-code queries), and doesn't specify prerequisites or exclusions.

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

• grok_chatB
  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. The description mentions flattening messages into a single prompt, which is useful context. However, it doesn't disclose important behavioral traits like authentication requirements, rate limits, error handling, or what the output looks like (though an output schema exists). For a tool with no annotation coverage, this leaves significant gaps in understanding how the tool behaves.

  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 perfectly concise with just two sentences. The first sentence states the core functionality, and the second sentence provides the key usage context. Every word earns its place with zero waste or redundancy.

  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 that there's an output schema (which handles return values) and no annotations, the description provides adequate basic context about what the tool does and when to use it. However, with 4 parameters and 0% schema description coverage, the lack of parameter guidance in the description creates a significant gap. The description is complete enough for understanding the tool's purpose but insufficient for effective parameter usage.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, meaning none of the 4 parameters have descriptions in the schema. The tool description doesn't mention any parameters at all, failing to compensate for the lack of schema documentation. While the description implies the 'messages' parameter is central, it provides no guidance on what 'model', 'raw_output', or 'timeout_s' do or how to use them effectively.

  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: 'Send a list of role/content messages to Grok by flattening into a single prompt.' This specifies the verb ('send'), resource ('messages to Grok'), and transformation ('flattening'). However, it doesn't explicitly differentiate from sibling tools like grok_code or grok_query, which likely handle different types of interactions.

  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 this tool: 'Useful for multi-turn context when the CLI only supports a single '-p' prompt.' This explains the specific scenario where this tool is valuable (multi-turn conversations with a CLI limitation). However, it doesn't explicitly mention when NOT to use it or provide alternatives to sibling tools.

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

• grok_queryB
  3.4/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden. It discloses that the tool returns 'the assistant's text' and mentions a 'raw_output' option for CLI output, adding some behavioral context. However, it doesn't cover critical aspects like error handling, rate limits, authentication needs, or what 'CLI headless mode' entails operationally.

  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 brief and front-loaded with the core purpose, followed by a specific usage tip. Both sentences earn their place by adding value, 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.

  Completeness3/5

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

  Given the complexity of a 4-parameter tool with no annotations and 0% schema coverage, the description is incomplete. It covers basic purpose and one parameter nuance, but lacks details on other parameters, error cases, or operational constraints. The presence of an output schema helps, but doesn't fully compensate for the gaps.

  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 0%, so the description must compensate. It adds meaning for 'raw_output' by explaining its effect ('to get raw CLI output and parsed messages'), but doesn't address other parameters like 'model', 'timeout_s', or 'prompt' beyond what the schema titles imply. This partial compensation meets the baseline for low 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 action ('Send a single prompt to Grok via CLI headless mode') and the resource (Grok), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'grok_chat' or 'grok_code', which likely have overlapping functionality with Grok interactions.

  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 provides some implied usage context by mentioning 'raw_output=true' for specific output formats, but it lacks explicit guidance on when to use this tool versus alternatives like 'grok_chat' or 'grok_code'. No exclusions or prerequisites are stated.

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