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list_structures

Extract structure names from loaded binaries to analyze data layouts and memory organization during reverse engineering.

Instructions

List all structure names from the loaded binary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • main.py:84-89 (handler)
    The handler function for the 'list_structures' tool. It is registered via the @mcp.tool() decorator and returns a list of structure names from the loaded Ghidra context JSON, checking if context is ready first.
    @mcp.tool()
    async def list_structures() -> list[str]:
        """List all structure names from the loaded binary."""
        if not ctx_ready:
            return ["❌ Context not ready. Run `setup_context()` first."]
        return [s["name"] for s in ctx.get("data_types", {}).get("structures", [])]
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe return format, pagination, sorting, error conditions, or performance characteristics. For a list operation with zero annotation coverage, this is insufficient.

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 immediately conveys the core functionality without unnecessary words. It's appropriately sized for a zero-parameter 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.

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 should provide more context about what 'structure names' means, how they're formatted, whether the list is complete or filtered, and what happens if no binary is loaded. The current description is too minimal for a tool that presumably returns structured data.

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 with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't waste space discussing parameters that don't exist, maintaining focus on the tool's purpose.

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 action ('List') and resource ('structure names from the loaded binary'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_enums' or 'list_functions', which would require more specific scope definition.

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 like 'get_structure' or other list tools. It doesn't mention prerequisites (e.g., whether a binary must be loaded first) or contextual constraints, leaving usage decisions ambiguous.

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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