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get_enum

Retrieve detailed information about a specific enumeration by name from binary files for reverse-engineering analysis.

Instructions

Get details of a specific enum by name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes

Implementation Reference

  • main.py:108-116 (handler)
    The handler function for the 'get_enum' MCP tool. It retrieves enum details by name from the loaded Ghidra context. The @mcp.tool() decorator registers the tool and infers the schema from the function signature and docstring.
    @mcp.tool()
    async def get_enum(name: str) -> dict:
        """Get details of a specific enum by name."""
        if not ctx_ready:
            return {"error": "Context not ready. Run `setup_context()` first."}
        for e in ctx.get("data_types", {}).get("enums", []):
            if e["name"] == name:
                return e
        return {"error": f"Enum '{name}' not found."}
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'gets details' but doesn't specify what those details include, whether it's a read-only operation, potential errors, or response format. This leaves significant gaps in understanding how the tool behaves.

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 with no wasted words. It's appropriately sized and front-loaded, clearly stating the core action without unnecessary elaboration.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what details are returned, potential behaviors, or how it fits with sibling tools, making it inadequate for a tool with one parameter and no structured support.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It mentions the parameter 'name' but doesn't add meaning beyond what the schema implies (e.g., format, examples, or constraints). This fails to address the coverage gap adequately.

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 verb ('Get details') and resource ('a specific enum by name'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_enums' or 'get_structure', which would require specifying what details are retrieved or how this differs from listing enums.

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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't specify when to use 'get_enum' instead of 'list_enums' or other sibling tools, nor does it mention prerequisites or contexts for usage.

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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