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yogeshkulkarni553

Content Server

listContentNames

Retrieve content names from an organization's database, with optional filtering to find specific entries.

Instructions

List all content names from the organization's database optionally filtered by name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoOptional name filter to search for specific content

Implementation Reference

  • Core implementation of the listContentNames tool handler. Calls rag_service to get contents filtered by optional name.
    def list_content_names(self, name: str | None = None) -> list[dict[str, Any]]:
        """
        List all content names from the organization's database optionally filtered by name.
    
        Args:
            name: Optional name filter to search for specific content
    
        Returns:
            List of content objects
        """
        return self.rag_service.get_all_contents(name, self.user_id_from_environment)
  • mcp_server.py:45-58 (registration)
    Tool registration in MCP list_tools handler, defining name, description, and input schema.
        name="listContentNames",
        description="List all content names from the organization's database optionally filtered by name",
        inputSchema={
            "type": "object",
            "properties": {
                "name": {
                    "type": "string",
                    "description": "Optional name filter to search for specific content"
                }
            },
            "additionalProperties": False
        }
    ),
    types.Tool(
  • JSON schema for input validation of listContentNames tool.
        "type": "object",
        "properties": {
            "name": {
                "type": "string",
                "description": "Optional name filter to search for specific content"
            }
        },
        "additionalProperties": False
    }
  • Dispatch handler in MCP call_tool that invokes the rag_tools.list_content_names method.
    if name == "listContentNames":
        result = rag_tools.list_content_names(arguments.get("name"))
        logger.debug(f"Tool {name} executed successfully")
        return [types.TextContent(type="text", text=str(result))]
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 states it's a list operation, implying read-only behavior, but doesn't address key aspects like whether it's paginated, rate-limited, requires authentication, or what the return format is. For a tool with no annotations, 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 a single, efficient sentence that front-loads the core purpose ('List all content names') and includes the optional filtering detail. There's no wasted text, 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 no annotations, no output schema, and a simple parameter, the description is incomplete. It doesn't explain what 'content names' entail (e.g., file names, titles), how results are returned, or any limitations. For a list tool with siblings offering similar functionality, more context 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.

Parameters3/5

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

The schema description coverage is 100%, with the single parameter 'name' documented as 'Optional name filter to search for specific content'. The description adds minimal value by restating this as 'optionally filtered by name', but doesn't provide additional context like wildcard support or case sensitivity. Baseline 3 is appropriate since the schema does the heavy lifting.

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: 'List all content names from the organization's database optionally filtered by name.' It includes a specific verb ('List'), resource ('content names'), and scope ('organization's database'), which makes the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'searchOrganizationContents', which might offer more advanced filtering or different output formats.

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 provides minimal guidance by mentioning optional filtering by name, but it doesn't specify when to use this tool versus alternatives like 'searchOrganizationContents'. There's no mention of prerequisites, performance considerations, or exclusions, leaving the agent with little context for tool selection among siblings.

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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