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rspace-os

RSpace MCP Server

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by rspace-os

tagDocumentOrNotebookEntry

Add tags to RSpace documents or notebook entries to organize research data and improve searchability by categorizing content with consistent labels.

Instructions

Adds tags to documents for organization and searchability

Usage: Categorize documents by project, experiment type, etc. Tags: Use consistent naming for better organization Returns: Updated document with new tags

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doc_idYes
tagsYesOne or more tags in a list

Implementation Reference

  • main.py:443-457 (handler)
    The core handler function for the 'tagDocumentOrNotebookEntry' tool. It uses the RSpace ELN client to update a document or notebook entry with the provided tags. The @mcp.tool decorator registers it with the exact name.
    @mcp.tool(tags={"rspace"}, name="tagDocumentOrNotebookEntry")
    def tag_document(
            doc_id: int | str,
            tags: Annotated[List[str], Field(description="One or more tags in a list")]
    ) -> Dict[str, any]:
        """
        Adds tags to documents for organization and searchability
        
        Usage: Categorize documents by project, experiment type, etc.
        Tags: Use consistent naming for better organization
        Returns: Updated document with new tags
        """
        resp = eln_cli.update_document(document_id=doc_id, tags=tags)
        return resp
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions that the tool 'Adds tags' (implying a mutation) and 'Returns: Updated document with new tags,' but it lacks details on permissions, whether tags are appended or replaced, error handling, or rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in behavioral disclosure.

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: the first sentence states the purpose, followed by usage and return details in bullet-like sections. Every sentence adds value, though it could be more structured (e.g., separating usage from returns). There's no wasted text, making it efficient.

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 complexity (a mutation tool with 2 parameters), no annotations, and no output schema, the description is incomplete. It covers basic purpose and usage but lacks critical details: no behavioral traits (e.g., side effects, auth needs), incomplete parameter guidance, and no output format beyond a vague 'Updated document.' This leaves gaps for an AI agent to invoke the tool correctly.

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 50% (only 'tags' has a description). The description adds minimal parameter semantics: it implies 'tags' are for 'organization and searchability' and suggests 'consistent naming,' but doesn't explain 'doc_id' or provide format details. With low schema coverage, the description partially compensates but doesn't fully bridge the gap for the undocumented 'doc_id' parameter.

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 tool's purpose: 'Adds tags to documents for organization and searchability.' It specifies the verb ('adds'), resource ('tags to documents'), and benefit ('organization and searchability'). However, it doesn't explicitly differentiate from sibling tools like 'search_by_tags' or 'update_document', which might also involve tags or document updates.

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 description provides implied usage guidelines: 'Categorize documents by project, experiment type, etc.' and 'Use consistent naming for better organization.' This suggests when to use the tool (for categorization) and best practices, but it doesn't explicitly state when not to use it or name alternatives like 'update_document' for broader modifications or 'search_by_tags' for querying.

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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