Generate Ent schemas

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

The description adds value beyond annotations by detailing the return format (JSON object with filename and source) and suggesting the agent write each file. This aligns with the readOnlyHint annotation (read operation) and provides actionable behavioral context.

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 paragraph that efficiently covers purpose, output, constraints, and action hint. No unnecessary information, and it is front-loaded with the core purpose.

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 and the presence of an output schema, the description covers key aspects: output format, file content details, and a known gap. Minor omissions include error handling and prerequisites, but overall sufficient for an agent with readOnlyHint context.

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 only 50% schema coverage, the description fails to explain the 'schema' parameter beyond what the schema provides (just its type). The 'database' parameter has a good description in the schema, but the description does not compensate for the lacking parameter documentation.

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 reads a PostgreSQL schema and emits Ent (Go) Schema struct files, one per table. It uses specific verbs (read, emit) and resource (PostgreSQL schema), and the output is distinct from sibling tools like generate_diesel_schema.

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 explicitly state when to use this tool over alternatives. It implies usage when Ent schemas are needed, but lacks guidance on exclusions or comparisons with other schema generators. The mention of composite FK gap is useful but not enough.

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