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generate_fastapi_models

Create Pydantic models and SQLAlchemy ORM models with relationships by providing entity names and relation formats, saving time on FastAPI model scaffolding.

Instructions

Generate Pydantic models and SQLAlchemy ORM models with relationships (Pro feature)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoAPI key for authentication
entitiesYesEntity names to model
relationshipsNoRelationships as 'EntityA->EntityB:type' format
Behavior2/5

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 does not say whether the tool writes files, overwrites existing models, requires an API key for the Pro feature, or returns generated code as output. The phrase 'Generate... models' implies creation but leaves the side effects and operational requirements unclear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One tightly packed sentence that front-loads the core purpose and includes the notable 'Pro feature' caveat. There is no filler, repetition, or unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Although the schema covers parameters, there is no output schema and no annotations, so the description should explain what the tool produces or modifies. It is missing key operational context: whether files are generated in-place, whether an existing project structure is required, how the API key is used, and what the turnaround or failure behavior looks like. This is a meaningful gap for an agent deciding whether and how to invoke the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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, including the 'EntityA->EntityB:type' format for relationships. The description adds a high-level connection between the 'relationships' parameter and the generated relationship support, but it does not materially deepen meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Generate') and concrete resource types ('Pydantic models and SQLAlchemy ORM models'), plus a distinguishing capability ('with relationships'). This clearly differentiates it from sibling tools like generate_fastapi_router and scaffold_fastapi_project without needing to inspect their schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The intended use—when you need FastAPI model classes—is implied by the description, but there is no explicit guidance about when to choose this tool over related siblings such as generate_fastapi_router or scaffold_fastapi_project, and no mention of prerequisites. The 'Pro feature' hint provides only a licensing context, not usage direction.

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

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