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get_graph_ids

Retrieve all stored graph IDs to access and manage network data for visualization and analysis.

Instructions

Get a list of all stored graph IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The @mcp.tool() decorated async function get_graph_ids() that returns the list of keys from the global graph_cache dictionary. This is the core handler logic for the tool and also serves as its registration via the decorator.
    @mcp.tool()
    async def get_graph_ids() -> List[str]:
        """Get a list of all stored graph IDs."""
        return list(graph_cache.keys())
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Get a list' implies a read-only operation, it doesn't specify whether this requires authentication, has rate limits, returns paginated results, or what format the list comes in. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 states exactly what the tool does with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information.

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?

For a zero-parameter tool that simply retrieves IDs, the description is adequate but has clear gaps. Without annotations or output schema, it doesn't specify what format the list returns (e.g., array of strings/numbers), whether it's paginated, or any authentication requirements. The description is minimally viable but incomplete for full contextual understanding.

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 schema description coverage is 100% (though trivial since there are no parameters). The description appropriately doesn't discuss parameters since none exist, which is correct for this case. Baseline for zero parameters is 4.

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 with a specific verb ('Get') and resource ('list of all stored graph IDs'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'get_graph_info' which might retrieve different graph-related information, 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 provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_graph_info' that likely retrieve different graph data, there's no indication of when this tool is appropriate or what distinguishes it from similar 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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