Agent skill

theorem-prover-interface

Interface with interactive theorem provers for mechanized verification

a5c.ai1,642★ · 1 repos on radarProfile →
claude-codecodexcan modify filesMIT
Install
npx skills add a5c-ai/babysitter --skill theorem-prover-interface --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Allowed tools: -Bash-Read-Write-Edit-Glob-Grep
Path: library/specializations/domains/science/computer-science/skills/theorem-prover-interface/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,642
Language: JavaScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Theorem Prover Interface ## Purpose Provides expert guidance on using interactive theorem provers for mechanized formal verification. ## Capabilities - Coq proof script generation - Isabelle/HOL interface - Lean 4 integration - Proof automation (hammers, tactics) - Proof library search - Extraction to executable code ## Usage Guidelines 1. **Prover Selection**: Choose appropriate theorem prover 2. **Formalization**: Formalize definitions and theorems 3. **Proof Development**: Develop proofs interactively 4. **Automation**: Apply automated tactics 5. **Extraction**: Extract certified code if needed ## Tools/Libraries - Coq - Isabelle - Lean - ACL2

What's inside
Steps it walks through
  1. Purpose
  2. Capabilities
  3. Usage Guidelines
  4. Tools/Libraries
More from babysitter
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About this skill
What does the theorem-prover-interface skill do?

Interface with interactive theorem provers for mechanized verification

How do I install it?

Run `npx skills add a5c-ai/babysitter --skill theorem-prover-interface --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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