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name: ghidra-refine description: "Extract pseudo-code with Ghidra and refine it with the LLM4Decompile V2 model family." metadata: disco-role: operating disable-model-invocation: true license: NOASSERTION

Ghidra Refinement

Use this sub-skill when the user wants to run the repo's refinement path: extract per-function pseudo-code with the bundled decompiler postscript and feed that pseudo-code into a V2 refinement model.

Covers

• headless extraction with the repo's bundled postscript helper
• pseudo-code dump parsing and prompt construction
• V2 refinement using LLM4Binary/llm4decompile-6.7b-v2 or related V2 checkpoints
• demo-style compile → extract → refine loops

Excludes

• direct assembly-only inference and benchmark scoring → use evaluation
• training or dataset preparation → use training
• SK²Decompile RL or BringUpBench → use sk2decompile

Start Here

1. Read references/ghidra-workflow.md for the two-stage flow.
2. Read references/data-formats.md before changing the pseudo-code dump or prompt shape.
3. Read references/troubleshooting.md if Java, Ghidra, or the model selection fails.
4. Use the bundled scripts in this sub-skill's scripts/ directory rather than the source checkout.

Common routes

Pseudo-code extraction

Use this route when the user needs the raw Ghidra output or wants to batch decompile a binary.

Good entry points:

• scripts/dump_pseudo.py
• scripts/run_demo.py

V2 refinement

Use this route when the user already has pseudo-code and wants the model to improve readability or syntax.

Good entry points:

• scripts/run_demo.py

Environment signals

• Java 17 may be required by the surrounding demo flow, depending on the headless backend the user actually has installed.
• The repo's example scripts mix Ghidra naming with decompiler-specific postscript APIs; verify the backend pair before running.
• clang-format is needed when pseudo-code normalization is part of the flow.
• The V2 model family is the normal target for refinement.

When to read the bundled references

• Use the workflow reference for the stage ordering and file expectations.
• Use the data-format reference to preserve the function delimiters and prompt wrapper.
• Use the troubleshooting reference when Ghidra or the refinement model fails.