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 describes the tool's function (RAG query with response generation) and mentions required parameters, but lacks details on authentication needs (though 'api_key' is implied), rate limits, error handling, or what happens if corpus keys are invalid. It adds some context but falls short of comprehensive behavioral traits.

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

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

The description is well-structured with a clear opening sentence, followed by an 'Args:' section detailing parameters and a 'Returns:' section. It is appropriately sized for a complex tool with many parameters, though some sentences could be more concise (e.g., the parameter explanations are verbose but necessary).

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

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

Given the tool's complexity (9 parameters, no annotations, no output schema), the description is partially complete. It covers the purpose, parameters, and return statement, but lacks information on output format, error cases, or dependencies. Without an output schema, more detail on the response structure would improve completeness for such a multifaceted tool.

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

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

The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose, required status, and default values (e.g., 'query: str, The user query to run - required'), compensating fully for the schema's lack of descriptions. This is essential given the 9 parameters with only 1 required.

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

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

The description clearly states the tool's purpose with specific verbs ('Run a RAG query using Vectara') and resources ('returning search results with a generated response'). It distinguishes from the sibling tool 'search_vectara' by emphasizing the generation of a response alongside search results, which suggests 'search_vectara' might only return raw search results without generation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 (for RAG queries with Vectara) and includes guidance on required parameters like asking the user for corpus keys. However, it does not explicitly state when NOT to use it or mention alternatives like 'search_vectara' for non-generation searches, which would be needed for a perfect score.

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

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

No annotations are provided, so the description carries full burden. It discloses that the tool performs a semantic search and returns matching results, but lacks details on behavioral traits like authentication needs (though 'api_key' is a parameter), rate limits, error handling, or what 'without generation' entails operationally. The description doesn't contradict annotations (none provided), but offers minimal behavioral context beyond basic functionality.

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

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

The description is well-structured with a clear purpose statement followed by 'Args:' and 'Returns:' sections. It's appropriately sized, with each sentence adding value (e.g., explaining parameters and returns). However, it could be more front-loaded by integrating key parameter details into the initial statement, and some phrasing is slightly verbose (e.g., 'Please ask the user to provide').

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

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

Given 6 parameters, 0% schema coverage, no annotations, and no output schema, the description is moderately complete. It covers parameter semantics well but lacks behavioral transparency (e.g., auth, limits) and detailed return value explanation beyond 'including the matching search results.' For a search tool with multiple parameters and no structured support, more context on outputs and behavior would improve completeness.

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

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 significant meaning beyond the schema by explaining all 6 parameters: purpose (e.g., 'query' is 'The user query to run'), requirements (e.g., 'corpus_keys' and 'api_key' are 'required'), defaults (e.g., 'n_sentences_before' default is 2), and user guidance (e.g., 'Please ask the user to provide one or more corpus keys'). This fully documents parameter semantics not covered by the schema.

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

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

The description clearly states the tool's purpose: 'Run a semantic search query using Vectara, without generation.' It specifies the verb ('search'), resource ('Vectara'), and distinguishes it from sibling 'ask_vectara' by noting 'without generation.' However, it doesn't explicitly contrast with the sibling tool beyond this implicit distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by stating 'without generation,' suggesting this is for pure search versus generative queries. It mentions 'Please ask the user to provide one or more corpus keys' for the 'corpus_keys' parameter, offering some guidance. However, it lacks explicit when-to-use versus 'ask_vectara' or other alternatives, and no exclusions are provided.

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