Server Quality Checklist

Tool Scores

• embed_textC
  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 the basic function but doesn't cover important traits such as rate limits, authentication needs, error handling, or what the embeddings represent (e.g., model used, dimensions). This leaves significant gaps for a tool that likely interacts with external APIs.

  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 with no wasted words. It is front-loaded with the core action and resource, making it easy to parse quickly, which is ideal for 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 complexity of generating embeddings (involving external API calls) and the lack of annotations and output schema, the description is incomplete. It doesn't address return values, error cases, or operational constraints, making it inadequate for safe and effective tool invocation by an 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?

  The schema description coverage is 0%, so the description must compensate. It mentions 'array of texts', which aligns with the 'texts' parameter in the schema, adding some meaning. However, it doesn't explain details like text length limits, encoding, or handling of empty strings, so it only partially compensates for the lack of schema descriptions.

  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 ('Generate') and resource ('OpenAI embeddings for an array of texts'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'index_documents' or 'vector_search', which might also involve embeddings, so it doesn't reach the highest score.

  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 like 'index_documents' or 'vector_search'. It lacks context on use cases, prerequisites, or exclusions, leaving the agent without clear usage instructions.

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

• index_documentsC
  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 mentions embedding and indexing but doesn't clarify whether this is a write operation, what permissions are needed, if it's idempotent, or what happens on failure. For a tool that likely modifies data, 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 extremely concise—a single sentence with zero wasted words. It's front-loaded with the core purpose and efficiently communicates the essential action without 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?

  Given the complexity of embedding and indexing operations, no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It lacks crucial details about behavior, error handling, return values, and how it differs from sibling tools, making it inadequate for safe and effective use.

  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?

  The schema description coverage is 0%, so the description must compensate, but it adds no information about the 'docs' parameter beyond what the schema structure implies. The description doesn't explain what 'docs' should contain, how documents are processed, or any constraints. With 1 parameter and no schema descriptions, baseline 3 is appropriate as the description doesn't add meaningful semantic context.

  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 ('Embed and index') and the target resource ('documents into Chroma'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'embed_text' or 'vector_search', which likely handle different aspects of the Chroma workflow.

  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 like 'embed_text' or 'vector_search'. There's no mention of prerequisites, use cases, or exclusions, leaving the agent to infer usage from the tool name alone.

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

• vector_searchB
  3.3/5.0
  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 mentions the technology (embeddings + Chroma) and optional filtering, but doesn't describe important behavioral traits like: whether this is read-only or has side effects, performance characteristics, error conditions, authentication requirements, or what the output format looks like. For a search tool with no annotation coverage, this leaves significant gaps.

  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 extremely concise at just two short sentences with zero wasted words. The first sentence establishes core functionality, the second adds important parameter context. Every element earns its place, and the information is front-loaded with the primary purpose stated immediately.

  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 3 parameters with 0% schema coverage, no annotations, no output schema, and a nested object parameter ('where'), the description is incomplete. It doesn't explain what the search returns, how results are ranked, what metadata can be filtered, or any limitations. For a semantic search tool with these contextual factors, the description should provide more operational context.

  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?

  With 0% schema description coverage, the description must compensate for all parameter documentation. It explicitly mentions the 'where' parameter's purpose ('metadata filter') and implies 'query' is for semantic search. While it doesn't mention 'topK', the description of 'Semantic search' combined with the parameter name strongly suggests it controls result count. This provides meaningful context beyond the bare schema.

  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 performs 'Semantic search using embeddings + Chroma' which is a specific verb (search) with technology context. It distinguishes from sibling tools 'embed_text' (creating embeddings) and 'index_documents' (adding to index) by focusing on retrieval/search functionality. However, it doesn't explicitly contrast with these siblings in the description text itself.

  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 usage context through 'Semantic search using embeddings' and mentions 'Optional metadata filter via `where`' which suggests when to use the where parameter. However, there's no explicit guidance on when to choose this tool versus alternatives like traditional keyword search tools that might exist elsewhere, nor does it mention prerequisites like needing indexed documents first.

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