Server Quality Checklist

Tool Scores

• aichat_create_conversation_v2C
  2.3/5.0
  Behavior2/5

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

  With no annotations, the description carries the full burden of disclosing behavior, but it only names the endpoint. It does not mention that the tool can mutate, retrieve, delete, or run asynchronous chat workflows, nor does it describe side effects or prerequisites.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness2/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is short and front-loaded, but it is under-specified rather than appropriately concise. A single generic sentence is not enough for a 22-parameter, multi-action tool.

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

  Completeness1/5

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

  Given the high complexity—22 parameters, five action modes, and no annotations—the description is severely incomplete. It does not explain how actions map to parameters, when each action is appropriate, or what the tool actually returns, leaving the agent to infer almost everything from the schema.

  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%, and the schema already documents each parameter, so the baseline is 3. The description itself adds no parameter-level semantics beyond what the schema provides.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose3/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description states a verb and resource ('Create/manage conversations via AiChat v2 endpoint'), so the general domain is clear. However, 'manage' is vague and does not reveal that the tool actually supports five distinct operations (chat, retrieve, retrieve_batch, update, delete). It also does not distinguish this v2 tool from the sibling aichat_create_conversation.

  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?

  There is no guidance on when to use this tool versus aichat_create_conversation or the other siblings. No when-to-use, when-not-to-use, or alternative selection guidance is provided.

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

• aichat_create_conversationA
  3.6/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the disclosure burden. It states that the tool sends a question, returns an answer, and can continue a conversation via conversation_id, plus the JSON response shape. It does not disclose side effects, cost/auth implications, or error behavior, though some stateful semantics are covered in 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-structured, front-loaded with the core purpose, and uses clear bullets for usage guidance. It is slightly repetitive in places, such as 'sends a question' followed by 'you need to ask a question to an AI model,' but overall it remains appropriately sized and scannable.

  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?

  With a rich input schema, full parameter descriptions, and an output schema, the description is largely complete for basic invocation. It covers primary use cases and return shape, but it could be more complete by addressing how to choose between this tool and aichat_create_conversation_v2.

  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 six parameters well. The description adds model family examples and conversation-continuation context, but it does not add substantive parameter meaning beyond what the input schema already provides.

  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 that the tool creates an AI conversation, sends a question to a model, and returns the generated answer. It distinguishes itself from aichat_list_models and aichat_get_usage_guide, but it does not differentiate itself from the sibling tool aichat_create_conversation_v2.

  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 explicit 'Use this when' bullets covering asking a question, continuing an existing conversation, and requesting specific model families. However, it does not mention when to avoid this tool or when aichat_create_conversation_v2 would be a better choice, so it lacks explicit alternatives.

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

• aichat_list_modelsA
  4.1/5.0
  Behavior3/5

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

  No annotations provided. Description indicates it returns a formatted list with descriptions, but doesn't discuss potential behaviors like rate limits or pagination. Adequate for a simple read-only operation.

  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?

  Concise, front-loaded with the action ('List all available AI models'), and each sentence adds value. No wasted words.

  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?

  Given zero parameters and a simple purpose, the description covers all needed information. Output schema exists, so return values are handled. Context signals indicate high schema coverage and no nested objects.

  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?

  No parameters exist, so baseline is 4. Description does not need to add parameter semantics.

  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 'List all available AI models for the AiChat API' and provides specific examples (GPT-4/5, o-series, etc.). It distinguishes from sibling tools (create_conversation, usage_guide) by focusing on listing models.

  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?

  No explicit guidance on when to use this tool versus alternatives. However, with zero parameters and a straightforward purpose, usage is implied (e.g., before creating a conversation).

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

• aichat_get_usage_guideA
  4.3/5.0
  Behavior3/5

  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 the tool returns a 'Complete usage guide' but does not explicitly declare idempotence or lack of side effects. For a simple read-only tool, this is adequate but could be more explicit.

  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 (3 short sentences), front-loads the purpose, and every sentence adds value. There is no waste, though the first two sentences are slightly redundant; still, the overall structure is excellent.

  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?

  Given the tool has no parameters and an output schema exists (per context), the description is complete. It clearly explains the return value ('Complete usage guide for AiChat tools'), which is sufficient for an agent to understand the tool's function.

  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 parameter semantics are not applicable. The description adds value by explaining what the tool returns (usage guide), which justifies the baseline score of 4 for tools with no parameters.

  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 purpose: 'Get a comprehensive guide for using the AiChat tools.' It distinguishes itself from sibling tools like aichat_create_conversation and aichat_list_models by focusing on documentation rather than actions.

  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 implies usage for obtaining guidance ('Provides detailed information on how to use the AiChat tools effectively'), but does not explicitly state when to use this versus alternatives or provide exclusions. Nonetheless, the context is clear.

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