Tencent SkillHub · AI

Acorn Prover

Verify and write proofs using the Acorn theorem prover for mathematical and cryptographic formalization. Use when working with Acorn proof files (.ac), verifying theorems, formalizing mathematical or cryptographic protocols, or writing proofs in the Acorn language. Triggers on: (1) Creating or editing .ac files, (2) Running acorn verify commands, (3) Formalizing math or crypto proofs, (4) Questions about Acorn syntax or standard library.

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: references/syntax.md, scripts/setup.sh, SKILL.md

Validation

Use the Yavira download entry.
Review SKILL.md after the package is downloaded.
Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

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I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

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I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.0

Provenance

Publisher: flyingnobita
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 10 sections Open source page

Setup (MUST DO WHEN RUNNING FIRST TIME)

If config.env does not exist in the skill directory: Ask the user for the following paths: ACORN_LIB - Path to acornlib (e.g., /path/to/acornprover/acornlib) ACORN_PROJECT - Path to project directory for .ac files (e.g., /path/to/acorn-playground) Verify the paths exist using list_dir or equivalent. If a path is invalid, inform the user and ask again. Run setup.sh with the validated paths: bash skills/acorn-prover/scripts/setup.sh "<ACORN_LIB>" "<ACORN_PROJECT>" Source the config to get ACORN_LIB, ACORN_PROJECT, and USE_MISE variables: source skills/acorn-prover/config.env If any of the above are blank / not set, inform the user to set the variable manually. If any of the above are changed, ask the user for new paths and run setup again.

Configuration

Config values are stored in skills/acorn-prover/config.env: VariableDescriptionACORN_LIBPath to acornlibACORN_PROJECTProject directory for .ac filesUSE_MISEtrue if mise is available

Verify Proofs

If USE_MISE=true: mise run acorn verify <filename>.ac Otherwise, use the direct CLI: acorn --lib "$ACORN_LIB" verify <filename>.ac

Reverify Proofs (CI/CD)

Check that all proofs are cached with no AI searches required: # With mise mise run acorn reverify # Or direct CLI acorn --lib "$ACORN_LIB" reverify Use for CI pipelines to ensure all proofs are complete.

Training Data Generation

Generate training data (problem-proof pairs) for AI model development: # With mise mise run acorn training ./training_data # Or direct CLI acorn --lib "$ACORN_LIB" training ./training_data Argument: DIR - Directory to output training data.

Documentation Generation

Generate library reference documentation: # With mise mise run acorn docs ./docs/library # Or direct CLI acorn --lib "$ACORN_LIB" docs ./docs/library Argument: DIR - Directory to output documentation.

Workflow

Source config: source skills/acorn-prover/config.env Write proof file in $ACORN_PROJECT/ Run the appropriate command (verify, reverify, training, docs) Always show the full command output to the user (success or error) Debug errors using the common errors table in references/syntax.md Iterate until verification passes

Quick Syntax Overview

from nat import Nat from add_comm_group import AddCommGroup // Theorems - auto-proved or with hints theorem example(a: Nat, b: Nat) { a < b implies a != b } // Typeclasses - axioms are named blocks, no "axiom" keyword typeclass A: AddGroup extends Zero, Neg, Add { inverse_right(a: A) { a + -a = A.0 } } // Structures structure Pair[T, U] { first: T second: U } // Inductive types - constructors MUST be lowercase inductive MyBool { tru fls } Key points: Built-in logic keywords (not, and, or, implies, iff, true, false) are reserved - do not redefine Constructor names must be lowercase Typeclass axioms use named blocks, not the axiom keyword

Standard Library (acornlib)

Key modules in $ACORN_LIB/src: ModuleContentsnat/Natural number axioms, induction, additionadd_group.acAddGroup with a + -a = A.0add_comm_group.acAbelian groups (AddCommGroup)

References

Full syntax, error table, examples: See references/syntax.md Context7 docs: Use context7 MCP with /acornprover/acorn or /acornprover/acornlib for latest documentation

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

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Package contents

Included in package

2 Docs1 Scripts

SKILL.md Primary doc
references/syntax.md Docs
scripts/setup.sh Scripts