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rspace-os

RSpace MCP Server

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by rspace-os

create_form

Define reusable templates for structured data entry in research workflows, enabling consistent capture of experiments, protocols, and reports with customizable fields.

Instructions

Creates a new custom form template for structured data entry

Usage: Define reusable templates for experiments, protocols, reports Fields structure: [ { "name": "Field Name", "type": "String|Text|Number|Radio|Date|Choice", "mandatory": True/False, "defaultValue": "optional default" } ] Returns: Created form information (form will be in NEW state)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
tagsNo
fieldsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • main.py:500-522 (handler)
    The handler function decorated with @mcp.tool for the 'create_form' MCP tool. It creates a new custom form in RSpace ELN by calling the client library's create_form method.
    @mcp.tool(tags={"rspace"})
    def create_form(
        name: str,
        tags: List[str] = None,
        fields: List[dict] = None
    ) -> dict:
        """
        Creates a new custom form template for structured data entry
        
        Usage: Define reusable templates for experiments, protocols, reports
        Fields structure:
        [
            {
                "name": "Field Name",
                "type": "String|Text|Number|Radio|Date|Choice", 
                "mandatory": True/False,
                "defaultValue": "optional default"
            }
        ]
        Returns: Created form information (form will be in NEW state)
        """
        return eln_cli.create_form(name=name, tags=tags, fields=fields)
  • main.py:500-500 (registration)
    Registration of the create_form tool using the FastMCP @mcp.tool decorator with rspace tag.
    @mcp.tool(tags={"rspace"})
  • main.py:89-90 (helper)
    Initialization of the ELN client used by the create_form handler.
    eln_cli = e.ELNClient(api_url, api_key)  # Electronic Lab Notebook operations
    inv_cli = i.InventoryClient(api_url, api_key)  # Inventory Management operations
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. It discloses that the created form will be in 'NEW state', which is valuable behavioral context not inferable from the schema. It also implies this is a write operation ('creates'), though it doesn't mention permissions, side effects, or error conditions that would be helpful for a mutation tool.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded with the core purpose. The usage context and parameter details are relevant and earned their place. However, the formatting of the fields structure example could be more concise, and there's some redundancy between 'structured data entry' and the fields explanation.

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?

Given this is a mutation tool with no annotations, 3 parameters, and an output schema exists, the description does well. It explains the purpose, usage context, parameter semantics for the most complex parameter, and return state. The main gap is not covering all parameters equally, but with an output schema handling return values, this is reasonably complete.

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?

With 0% schema description coverage, the description must compensate, and it does so effectively. It provides detailed semantics for the 'fields' parameter including structure, field types, mandatory flags, and default values. While it doesn't explicitly mention 'name' and 'tags' parameters, the schema coverage is so low that this level of detail for the complex 'fields' parameter earns full credit.

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 creates a 'new custom form template for structured data entry', specifying both the verb ('creates') and resource ('form template'). It distinguishes from siblings like 'create_sample' or 'create_document_from_form' by focusing specifically on form templates for data entry.

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 for usage ('Define reusable templates for experiments, protocols, reports'), giving practical examples of when to use this tool. However, it doesn't explicitly state when NOT to use it or mention alternatives among the many sibling tools, such as when to use 'create_sample_template' instead.

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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