skills/domains/math/lean-theorem-proving-guide/SKILL.md
LLM agent for formal theorem proving in Lean 4
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LeanAgent is an LLM-based agent for automated theorem proving in Lean 4, a modern proof assistant. It combines LLM reasoning with formal verification — proposing proof steps that are verified by Lean's type checker. Can prove novel theorems, not just benchmarks, by exploring proof strategies, backtracking on failures, and learning from successful proofs.
Theorem Statement (Lean 4)
↓
Goal Analysis Agent (understand proof obligations)
↓
Tactic Suggestion Agent (propose proof steps)
↓
Lean 4 Verification (check tactic correctness)
↓
Backtracking (if tactic fails, try alternatives)
↓
Proof or timeout
from lean_agent import LeanAgent
agent = LeanAgent(
llm_provider="anthropic",
lean_path="/path/to/lean4",
)
# Prove a theorem
result = agent.prove(
theorem="""
theorem add_comm (m n : Nat) : m + n = n + m := by
sorry
""",
max_attempts=50,
timeout=120,
)
if result.proved:
print("Proof found!")
print(result.proof)
else:
print(f"Failed. Best attempt:\n{result.best_attempt}")
print(f"Remaining goals: {result.remaining_goals}")
# Configure search strategy
agent = LeanAgent(
search_config={
"strategy": "best_first", # best_first, bfs, dfs
"max_depth": 20, # Max proof steps
"beam_width": 5, # Tactics to try per step
"temperature": 0.7, # LLM sampling temp
"backtrack_on_fail": True,
},
)
# Interactive proof mode
session = agent.interactive_prove(
theorem="theorem my_thm : ∀ n : Nat, n + 0 = n := by"
)
while not session.done:
print(f"Current goals:\n{session.goals}")
tactics = session.suggest_tactics(k=5)
for i, t in enumerate(tactics):
print(f" {i}: {t.tactic} (confidence: {t.score:.2f})")
# Agent automatically picks best tactic
session.step()
-- Common tactics LeanAgent uses:
-- intro, apply, exact, rfl, simp, omega
-- induction, cases, constructor, ext
-- rw, calc, have, let, show
-- Example theorem + proof
theorem list_append_nil (l : List α) : l ++ [] = l := by
induction l with
| nil => simp
| cons h t ih => simp [ih]
# Prove multiple theorems
theorems = [
"theorem t1 : 1 + 1 = 2 := by sorry",
"theorem t2 (n : Nat) : n + 0 = n := by sorry",
"theorem t3 (n m : Nat) : n + m = m + n := by sorry",
]
results = agent.prove_batch(
theorems=theorems,
parallel=True,
timeout_per=60,
)
for thm, result in zip(theorems, results):
status = "PROVED" if result.proved else "FAILED"
print(f"[{status}] {thm[:50]}...")
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