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

With no annotations, the description carries the full burden. It does mention that the tool returns source citations, which is helpful. However, it does not disclose whether the operation is read-only, what happens if no answer is found, or any potential side effects. The transparency is moderate but incomplete.

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 a single, concise sentence that directly conveys the primary purpose and output. There is no redundant information, and it is well-structured for quick understanding.

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?

The description mentions the output (source citations) but omits important operational context such as error handling, expected behavior when no answer exists, or the role of top_k. Since there is no output schema, the description is not required to detail return fields, but the lack of parameter explanation and behavioral details leaves room for ambiguity.

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 schema provides only titles ('Question', 'Top K') and no descriptions. The tool description does not elaborate on the parameters or their expected values. There is no explanation of what 'top_k' controls or how it affects the answer. The schema coverage is 0%, and the description adds no clarification.

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 function: answering a question from the knowledge base and returning source citations. It uses a specific verb ('answer') and resource ('knowledge base'), and the output is specified as citations, which distinguishes it from a generic search.

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 does not provide any guidance on when to use this tool versus the sibling search_knowledge_base. It does not explicitly state that this tool should be used when a direct answer with citations is needed, nor does it mention conditions or alternatives. Users must infer the distinction.

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 must convey behavioral traits on its own. It does not mention whether the operation is read-only, potential performance implications of listing 'all' documents, pagination, sorting, or any side effects. The description is overly minimal for full transparency.

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 a single, concise sentence that leads with the verb and object. It contains no filler or redundant information, making it efficiently structured and easy to parse.

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 that an output schema exists (as indicated), the description need not detail return values. It adequately communicates the tool's scope. Minor gaps remain, such as lack of mention of pagination or sorting, but these are not critical for a list operation and are likely covered by the output schema.

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?

With zero parameters, the baseline score is 4. There are no parameter semantics to describe, and the description correctly avoids inventing any. It adds no meaning beyond the schema because there is nothing to explain.

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 action ('List') and the resource ('all documents currently indexed by the RAG service'), making its purpose unambiguous. It distinguishes itself from siblings: search_knowledge_base for searching, ask_knowledge_base for querying, and service_health for health checks.

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 by stating what it lists, but it does not explicitly say when to use this tool over alternatives. There is no mention of conditions or exclusions, leaving the decision to inference rather than direct guidance.

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 the full burden. It discloses the main behavior (returns grounded chunks) but does not mention read-only nature, potential side effects, or error/limit behavior. 'Search' implies non-destructive, but this is not explicit.

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 a single concise sentence with no redundant information. It directly states the action, target, and output type.

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?

The description communicates the core function and output (grounded chunks) but lacks context on when to use it relative to siblings, output size limits, or query formatting. It is adequate for a simple search but not fully complete.

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 coverage by the description is 0% – no parameters are referenced. The mention of 'text, tables, and images' hints at modality but does not explain query, top_k, or valid modality values. The description fails to compensate for the schema's lack of detail.

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 'Search text, tables, and images in the indexed knowledge base, returning grounded chunks' uses a specific verb (search), identifies the resource (indexed knowledge base), and clearly differentiates from siblings like ask_knowledge_base (which implies answering) and list_documents (which implies enumeration).

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 (searching for relevant chunks) but does not explicitly state when to prefer this tool over ask_knowledge_base or list_documents. No alternative conditions are provided.

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 states what the tool does but does not disclose error behavior, side effects, or the exact meaning of 'available'. This is acceptable for a simple health check but leaves some behavioral details unspecified.

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 a single, clear sentence with no redundant words. It efficiently communicates the tool's purpose and output.

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?

For a tool with no input parameters and no output schema, the description is complete. It specifies the action (check availability) and the return value (index counts), sufficient for an agent to invoke it correctly.

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 schema has zero parameters, so description coverage of parameters is trivially complete. With no parameters, the description cannot add meaning beyond the schema, justifying the baseline score.

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 function: check availability of the linked RAG API and return index counts. The verb 'check' and 'return' specify actions, and the resource is explicit. It distinguishes from sibling tools (search, ask, list) by focusing on service health rather than content operations.

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 purpose implies when to use it (to verify service availability and get index counts), and its differentiation from siblings is clear. However, it does not explicitly mention alternatives or conditions for selection, so it falls short of fully explicit guidance.

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