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Lean ai formalization

Skill r-irbe/proof-skills/skills/lean-ai-formalization

APM-installable agent skills for Lean 4 and Mathlib4 — proof tactics, math domains, review and research workflows, generic tooling.

Install
npx -y skills add r-irbe/proof-skills --skill lean-ai-formalization

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USE FOR: Formal verification of AI systems — agentic AI safety, alignment, high-stakes AI, evolving agents, neural network properties, and AI governance constraints. Use when formalizing safety envelopes, trust dynamics, multi-agent composition, AI act compliance, reward specifications, alignment properties, or any AI system property that must be formally verified. DO NOT USE FOR: AI methodology itself (use @ai-high-stakes-verifiable or @ai-agentic-evolving); security-specific formalisation (use @lean-security-formalization); knowledge formalisation (use @lean-knowledge-formalization). TRIGGERS: AI formalization, agentic safety, alignment proof, high-stakes AI, neural network property, AI governance.

SKILL.md

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Lean 4 AI Systems Formalization

Guide to formally verifying properties of AI systems, from safety envelopes to alignment guarantees.


Routing

  • USE FOR: Formal verification of AI systems — agentic AI safety, alignment, high-stakes AI, evolving agents, neural network properties, and AI governance constraints. Use when formalizing safety envelopes, trust dynamics, multi-agent composition, AI act compliance, reward specifications, alignment properties, or any AI system property that must be formally verified.
  • DO NOT USE FOR: AI methodology itself (use @ai-high-stakes-verifiable or @ai-agentic-evolving); security-specific formalisation (use @lean-security-formalization); knowledge formalisation (use @lean-knowledge-formalization).
  • TRIGGERS: AI formalization, agentic safety, alignment proof, high-stakes AI, neural network property, AI governance.

Workflow

  1. Identify the AI property to formalise: safety, alignment, agentic invariant, or neural-network property.
  2. Pick the matching section of the body (verification framework, formal-property catalog, alignment-axiom set).
  3. Produce the Lean statement + proof skeleton; verify against the current Mathlib pin before delegating to @lean-proof.
  4. Hand off: to @lean-proof-review once the proof compiles, to @lean-enforcement for the CI gate, to @lean-zettelkasten for the pattern.

Recovery & STOP

  • STOP if the property has not been formally stated — delegate to @lean-specification first.
  • STOP if Mathlib does not yet have the needed primitives — escalate to @lean-research.
  • STOP if the AI system is agentic/emergent — delegate dynamics modelling to @ai-agentic-evolving first.

Handoffs

  • Predecessors: agent:gateway, skill:lean-research.
  • Successors: skill:lean-proof-review, skill:lean-enforcement, skill:lean-zettelkasten, skill:lean-doc-feedback.

Detailed reference

Full content for lean-ai-formalization lives in references/lean-ai-formalization-handbook.md. Load that file when the skill is convened; the SKILL.md only carries the dispatch contract and the parts index.

SectionTopic
Part 1AI Safety Properties
Part 2Agentic AI
Part 4High-Stakes AI Verification
Part 5Neural Network Properties
Part 6Multi-Agent Composition
Part 7Commonsense and Causal Reasoning
Part 8Research Council Integration

See also

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