Chain of States (CoS) Skill 🐸
Trit: -1 (MINUS - Validator)
GF(3) Triad: chain-of-states (-1) ⊗ proof-of-frog (0) ⊗ alife (+1) = 0
Overview
CoSProver framework for translating informal proofs to Lean4 via intermediate formal proof states.
From Wang et al. (2025): "Translating Informal Proofs into Formal Proofs Using a Chain of States"
Core Insight
Informal Proof (natural language)
↓ Stage 1: Extract CoS
Chain of States [s₀ → s₁ → ... → sₙ]
↓ Stage 2: Generate tactics
Formal Lean4 Proof
Key Observations:
- Informal proofs use logical transitions (implications/equivalences) without explicit intermediate states
- Lean requires explicit proof states + tactics connecting them
- CoS bridges this gap with explicit intermediate representations
Two-Stage Framework
Stage 1: CoS Extraction
"Let x > 0. Since x > 0, we have x² > 0."
↓
[⊢ x > 0 → x² > 0] → [h : x > 0 ⊢ x² > 0] → [⊢ True]
Stage 2: Tactic Generation
theorem sq_pos (x : ℝ) (h : x > 0) : x² > 0 := by
-- Tactic for s₀ → s₁
intro h
-- Tactic for s₁ → s₂
exact sq_pos_of_pos h
Connection to Proof-of-Frog
| CoS Concept | Proof-of-Frog Equivalent |
|---|---|
| Proof state sᵢ | Knowledge nugget |
| Tactic τᵢ | Frog leap |
| State transition | Eating a frog |
| Full proof | Pond traversal |
Frog Lifecycle as CoS
🥒 TADPOLE (s₀) -- Initial goal state
↓ τ₁ (intro)
🐸 FROGLET (s₁) -- Hypothesis introduced
↓ τ₂ (apply)
🦎 MATURE FROG (sₙ) -- QED
Implementation
Lean4 CoS Type
structure ProofState where
goal : Expr
context : List Expr
trit : Int -- GF(3) stage
structure ChainOfStates where
states : List ProofState
transitions : List Tactic
def cos_invariant (cos : ChainOfStates) : Prop :=
(cos.states.map (·.trit)).sum % 3 = 0
Python CoS Extraction
def extract_cos(informal_proof: str) -> List[ProofState]:
"""
Extract Chain of States from informal proof text.
Each state is a formal representation of proof progress.
"""
steps = segment_proof(informal_proof)
return [formalize_state(s) for s in steps]
Comparison to Chain-of-Thought
| Dimension | Chain-of-Thought (CoT) | Chain of States (CoS) |
|---|---|---|
| Target | Reasoning trace | Proof states |
| Granularity | Natural language | Formal expressions |
| Verification | None | Lean type checker |
| Composability | Weak | Strong (tactic composition) |
Performance (Wang et al. 2025)
| Benchmark | miniF2F | ProofNet |
|---|---|---|
| Direct generation | 36.2% | 18.4% |
| CoSProver | 42.8% | 24.1% |
| Improvement | +6.6% | +5.7% |
Usage
# Load skill
skill chain-of-states
# Extract CoS from informal proof
python cos_extract.py "Let n be even. Then n² is even."
# Generate Lean4 tactics
lean4 cos_to_tactics.lean
References
- Wang et al. (2025). "Translating Informal Proofs into Formal Proofs Using a Chain of States." arXiv:2512.10317
- Ahuja et al. (2024). "ImProver: Agent-Based Automated Proof Optimization" - Chain-of-States technique. arXiv:2410.04753
Либиди Фрог Connection
Либиди Фрог (Proof-of-Frog) + Chain of States = compositional proof verification:
proof-chain(-1) ⊗ proof-of-frog(0) ⊗ alife(+1) = 0 ✓
Where Chain of States provides the -1 (validator) role:
- Validates each state transition
- Ensures GF(3) conservation across proof steps
- Connects informal human reasoning to formal verification
Gay.jl Colors
using Gay
seed = gay_seed(2512) # arXiv paper ID
palette(3) # CoS triad colors
| Stage | Color | Meaning |
|---|---|---|
| Initial | #B0285F |
Unproven goal |
| Intermediate | #77DEB1 |
Progress state |
| Terminal | #8ADB6E |
QED |
Autopoietic Marginalia
The interaction IS the skill improving itself.
Every use of this skill is an opportunity for worlding:
- MEMORY (-1): Record what was learned
- REMEMBERING (0): Connect patterns to other skills
- WORLDING (+1): Evolve the skill based on use
Add Interaction Exemplars here as the skill is used.