A specialized tool for writing, verifying, and documenting formal mathematical and cryptographic proofs using the Acorn theorem prover.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install acorn-prover
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install acorn-prover using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Acorn Prover skill is a specialized module for Openclaw Skills designed to handle formal verification tasks. It enables AI agents to interact with the Acorn theorem prover, facilitating the creation of rigorous mathematical proofs and cryptographic protocols. By integrating these capabilities into Openclaw Skills, developers can automate the verification of .ac files, ensuring that complex logic is sound and reproducible.
This skill is particularly useful for developers who need to bridge the gap between AI-assisted coding and formal methods. It provides a structured workflow for sourcing libraries, managing project paths, and executing verification commands. Whether you are formalizing group theory or building secure cryptographic primitives, this tool provides the necessary infrastructure within the Openclaw Skills ecosystem.
To begin using this skill within Openclaw Skills, follow these configuration steps:
bash skills/acorn-prover/scripts/setup.sh "/path/to/acornlib" "/path/to/project"
source skills/acorn-prover/config.env
The skill manages its state and metadata through a configuration file and specific directory structures to ensure compatibility with Openclaw Skills.
| Component | Role in Openclaw Skills |
|---|---|
config.env |
Stores environment variables like ACORN_LIB and ACORN_PROJECT. |
ACORN_LIB |
Points to the source of standard axioms, such as natural numbers and group theory. |
.ac files |
Source files containing formal proof code and theorem definitions. |
training_data/ |
Target directory for problem-proof pairs generated for model development. |
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