json_entity

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the core function and options, but does not describe output format, error handling, limitations, or any side effects. For a generation tool, the absence of these details leaves significant ambiguity.

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, front-loaded sentence that conveys the core purpose and key options without unnecessary verbosity. Every word earns its place, and it fits well within a tool description.

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 is adequate for a moderate-complexity tool, covering the main inputs and outputs (entity class code). However, with no output schema and no annotations, it lacks details on the generated code's structure, possible limitations, or handling of edge cases. It is minimally sufficient but has clear gaps.

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 descriptions for most parameters (75% coverage), but the description explicitly clarifies the meaning of input_type (json/sql) and language (cs/java/go), which the schema's enum alone does not fully explain. This adds valuable context beyond the schema, especially for the undocumented input_type.

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: generating entity class code from JSON or SQL CREATE TABLE, and specifies the key options (input_type and language). This distinguishes it from sibling tools like json_convert or code_format, which serve different purposes.

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 the tool (when you need entity classes from JSON/SQL) but does not explicitly mention when not to use it or alternatives. Given the unique functionality among siblings, the usage context is clear, but it lacks explicit exclusions.

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