super_validate

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 effectively describes key traits: it's a non-executing validation tool (implying read-only and non-destructive), returns diagnostics with position information, and offers migration suggestions for specific error types. It does not mention rate limits, authentication needs, or detailed output format, but covers essential behavior adequately for a validation tool.

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 appropriately sized and front-loaded, consisting of a single, efficient sentence that conveys the core purpose, behavior, and output. Every word earns its place, with no redundant information or fluff, making it easy for an AI agent to parse and understand quickly.

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 (a validation tool with one parameter), no annotations, and no output schema, the description is mostly complete. It explains what the tool does, its non-executing nature, and the type of output (diagnostics with position info and migration suggestions). However, it lacks details on the exact format of the diagnostics or error types, which could be helpful for an agent to interpret results, preventing a perfect score.

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 input schema has 100% description coverage, with the single parameter 'query' documented as 'The SuperSQL query to validate'. The description adds no additional parameter semantics beyond this, such as query length limits or syntax examples. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract.

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 ('validate SuperSQL query syntax without executing') and distinguishes it from siblings like super_query (which likely executes queries) and super_test_compat (which might test compatibility). It explicitly mentions what it does not do (execute) and what it returns (diagnostics with position info and migration suggestions).

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 syntax validation and migration error checking, particularly for converting from 'zq' to SuperDB. However, it does not explicitly state when not to use it or name specific alternatives among the siblings (e.g., super_query for execution, super_test_compat for compatibility testing), which prevents a perfect score.

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