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list_obs

Retrieve key column names from single-cell RNA sequencing data for use in downstream analysis tasks.

Instructions

List key columns in adata.obs. It should be called before other tools need obs key column names input

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The core handler function for the 'list_obs' tool, which returns the list of observation (obs) column names from the AnnData object.
    def list_obs(adata):
        return list(adata.obs.columns)
  • Pydantic input schema model for the 'list_obs' tool. It is an empty model, indicating no input parameters are required.
    class ListObsModel(JSONParsingModel):
        """ListObsModel"""    
        pass    
  • MCP tool registration defining the 'list_obs' tool with its name, description, and input schema reference.
    list_obs_tool = types.Tool(
        name="list_obs",
        description="List key columns in adata.obs. It should be called before other tools need obs key column names input",
        inputSchema=ListObsModel.model_json_schema(),
    )
  • Dictionary collecting all utility tools including 'list_obs_tool', which is exposed via tool/__init__.py to the server.
    util_tools = {
        "mark_var": mark_var_tool,
        "list_var": list_var_tool,
        "list_obs": list_obs_tool,  
        "check_gene": check_gene_tool,
        "merge_adata": merge_adata_tool,
    }
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 of behavioral disclosure. It mentions the tool lists columns and should be called before other tools, but it doesn't describe what 'key columns' means, whether this is a read-only operation, if it has side effects, or details about output format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 two concise sentences that efficiently state the purpose and usage guidelines without any wasted words. It's front-loaded with the core function and follows with practical advice, making it easy to parse and understand quickly.

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

Completeness3/5

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

Given the tool has 0 parameters, no annotations, and no output schema, the description provides basic purpose and usage but lacks details on what 'key columns' are, the output format, or how it integrates with the broader context of sibling tools. It's minimally adequate but has clear gaps in explaining the tool's role and results.

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 0 parameters, and the input schema has 100% description coverage (though it's generic as 'ListObsModel'). The description doesn't need to add parameter details, so it appropriately focuses on usage. A baseline of 4 is given since no parameters are present, and the description doesn't attempt to explain non-existent parameters.

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

Purpose3/5

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

The description states the tool 'List key columns in adata.obs', which provides a specific verb ('List') and resource ('key columns in adata.obs'), but it's somewhat vague about what constitutes 'key columns' and doesn't clearly distinguish this from sibling tools like 'list_var' or 'read_tool' that might also list data. It avoids tautology by not just restating the name.

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 explicitly states 'It should be called before other tools need obs key column names input', providing clear context on when to use this tool (as a prerequisite for other operations). However, it doesn't specify when not to use it or name alternatives among siblings, such as how it differs from 'list_var' or other data inspection tools.

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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