query_datasf

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 key behavioral traits: execution of SoQL queries, support for auto-correction, and JSON return format. However, it lacks details on error handling, rate limits, authentication needs, or side effects, which are important for a query tool with no structured annotations.

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, well-structured sentence that efficiently conveys purpose, key feature (auto-correction), and output format (JSON). It is front-loaded with the main action and avoids unnecessary details, making it highly concise and effective.

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 no annotations and no output schema, the description is moderately complete. It covers the tool's purpose and basic behavior but lacks details on error responses, pagination, or result structure, which would be helpful for an AI agent to use the tool effectively in complex scenarios.

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 100%, so the schema already documents all parameters thoroughly. The description adds marginal value by mentioning auto-correction in context, but does not provide additional semantic details beyond what the schema specifies (e.g., examples of SoQL queries or auto-correction behavior).

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 verb 'Execute' with the resource 'a SoQL query against a dataset', specifies the language (SoQL), and mentions auto-correction and JSON return format. It distinguishes from siblings like get_schema (metadata) and list_datasf/search_datasf (likely list/search operations) by focusing on query execution.

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 for querying datasets with SoQL, but does not explicitly state when to use this tool versus alternatives like search_datasf or list_datasf. It mentions auto-correction as a feature, which provides some context, but lacks explicit guidance on scenarios or exclusions.

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