clearskies MCP Server

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scaffold_project

Generate a complete clearskies project with models and endpoints, providing full working application code.

Instructions

Generate a complete clearskies project with models and endpoints.

Returns the full file content for a working clearskies application.

Args:
    project_name: The name of the project/application.
    models: List of model definitions. Each dict has:
        - name (str): Model class name in PascalCase
        - columns (list[dict]): Column definitions (same format as generate_model)
        - backend_type (str, optional): Backend type (default: "MemoryBackend")
        - id_column_name (str, optional): Id column name (default: "id")
        - url (str, optional): URL path for the REST API
        - readable_column_names (list[str], optional): Readable columns
        - writeable_column_names (list[str], optional): Writeable columns
        - sortable_column_names (list[str], optional): Sortable columns
        - searchable_column_names (list[str], optional): Searchable columns
        - default_sort_column_name (str, optional): Default sort column
    context_type: The context type to use (default: "WsgiRef").
    endpoint_type: Endpoint type to use (default: "RestfulApi").

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_name": "<project_name>",
      "models": "<models>"
    },
    "name": "scaffold_project"
  }
}

Input Schema

Name	Required	Default
`models`	Yes
`context_type`	No	WsgiRef
`project_name`	Yes
`endpoint_type`	No	RestfulApi

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.2Aug 2, 2026

TDQS

A4.5/5.0

Behavior4/5

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 states that the tool 'Returns the full file content for a working clearskies application,' which clarifies that it returns generated content rather than performing side effects like writing files. This is a useful behavioral trait beyond the schema. However, it does not mention input validation, error cases, or any other runtime behaviors, so it is not fully comprehensive.

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?

The description is well-structured: a one-sentence purpose, a brief note on return value, and then a detailed Args section. Every sentence provides necessary information, and the detailed model structure is essential for correct usage. It is appropriately sized for the complexity of the tool and avoids fluff.

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

Completeness4/5

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

The tool is complex with 4 parameters (one deeply nested), and the description covers all of them with defaults and sub-fields. It also references 'same format as generate_model' for column definitions, which helps link to sibling tools. However, it does not explicitly state which fields within the models dict are required (e.g., name and columns appear necessary but are not marked as required), which could lead to incomplete model definitions. With an output schema present, return value explanation is justifiably minimal.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides only parameter names and types with no descriptions (0% coverage). The description compensates fully by explaining each parameter, including defaults for context_type and endpoint_type, and an extensive breakdown of the models parameter structure with fields like name, columns, backend_type, id_column_name, url, and various column name lists. This adds enormous meaning beyond the sparse 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 clearly states the tool's purpose: 'Generate a complete clearskies project with models and endpoints.' It uses a specific verb ('Generate') and resource ('clearskies project'), and explicitly distinguishes itself from sibling tools like generate_model and generate_endpoint by focusing on the complete project rather than individual components.

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

Usage Guidelines4/5

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

The description provides clear context: use this to generate a complete project with models and endpoints. It does not explicitly name alternatives or exclusion scenarios, but the phrase 'complete clearskies project' implies the intended use case. Since the schema and sibling names offer context, this is clear but not exhaustive.

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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