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penpot_schema

Retrieve the Penpot API schema in JSON format to understand available endpoints and data structures for programmatic design workflows.

Instructions

Provide the Penpot API schema as JSON.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'penpot_schema' tool, which loads the Penpot schema JSON file from the resources path and returns it as a dictionary.
    def penpot_schema() -> dict:
        """Provide the Penpot API schema as JSON."""
        schema_path = os.path.join(config.RESOURCES_PATH, 'penpot-schema.json')
        try:
            with open(schema_path, 'r') as f:
                return json.load(f)
        except Exception as e:
            return {"error": f"Failed to load schema: {str(e)}"}
  • Registration of the 'penpot_schema' tool using the MCP decorator.
    @self.mcp.tool()
  • Identical handler function registered as a resource 'penpot://schema', providing the same schema loading logic.
    def penpot_schema() -> dict:
        """Provide the Penpot API schema as JSON."""
        schema_path = os.path.join(config.RESOURCES_PATH, 'penpot-schema.json')
        try:
            with open(schema_path, 'r') as f:
                return json.load(f)
        except Exception as e:
            return {"error": f"Failed to load schema: {str(e)}"}
  • Registration of the penpot_schema as an MCP resource.
    @self.mcp.resource("penpot://schema", mime_type="application/schema+json")
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 states what the tool does but fails to describe key traits such as whether it's a read-only operation, potential rate limits, authentication needs, or what the JSON output structure entails. This leaves significant gaps in understanding the tool's behavior.

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 a single, direct sentence that efficiently conveys the core function without any wasted words. It is front-loaded with the essential information, making it highly concise and well-structured for quick comprehension.

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?

Given the tool's simplicity (0 parameters, no output schema), the description is minimal but insufficient. It lacks context about the schema's scope (e.g., full API vs. partial), format details, or how it differs from 'penpot_tree_schema'. Without annotations or output schema, more completeness is needed to guide effective use.

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

Parameters4/5

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

The tool has zero parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter details, so it appropriately avoids redundancy. A baseline of 4 is applied since no parameters exist, and the description doesn't mislead about inputs.

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

Purpose4/5

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

The description clearly states the action ('Provide') and resource ('Penpot API schema as JSON'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'penpot_tree_schema', which appears to serve a similar schema-related function, preventing a perfect score.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool versus alternatives like 'penpot_tree_schema' or other schema-related operations. It lacks context about prerequisites, timing, or comparisons with sibling tools, leaving the agent without 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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