__  __       _   _     _____       _     _
          |  \/  | __ _| |_| |__ | ____|_   _(_) __| | ___ _ __   ___ ___
          | |\/| |/ _` | __| '_ \|  _| \ \ / / |/ _` |/ _ \ '_ \ / __/ _ \
          | |  | | (_| | |_| | | | |___ \ V /| | (_| |  __/ | | | (_|  __/
          |_|  |_|\__,_|\__|_| |_|_____| \_/ |_|\__,_|\___|_| |_|\___\___|

External computation in. Lean theorems out.

MathEvidence turns results from external solvers into Lean-checked evidence: adapters propose; Lean decides. SymPy and Mathematica adapters, an Agent API, and Studio surfaces share one idea — use powerful external tools without trusting them inside the theorem prover.

Experimental research preview: no capability is stable. See known limitations before relying on results.

Why it exists

Formal work often needs exact algebra, search, or symbolic computation that mature external systems already do well. One-off bridges reinvent translation and trust boundaries — and can smuggle unchecked solver answers into proofs.

MathEvidence offers a shared path: an explicit semantic contract, checkable evidence, and a reusable Lean theorem.

Do not trust the solver. Lean checks the evidence.

Quick start

Needs: Lean matching lean-toolchain, Python 3 with the repo requirements, and just.

git clone https://github.com/fraware/MathEvidence.git
cd MathEvidence
just check

That runs the local build and test gate. Full walkthrough: docs/getting-started/.

Optional: SymPy for open backends; wolframscript (set MATHEVIDENCE_WOLFRAMSCRIPT) for live Mathematica. Bundles under evidence/ replay offline without a live CAS.

Try one example

Open the committed rational-equality example (x^2 - 1)/(x - 1) = x + 1 (with an explicit denominator condition):

evidence/examples/rational_equality_basic/

Inspect request.cjson, certificate.cjson, and theorem.lean. Lean owns acceptance; the adapter is untrusted. Then follow docs/getting-started/ for offline replay, or start the local Agent API:

python -m agent.api.server --host 127.0.0.1 --port 8787

Health check: GET http://127.0.0.1:8787/v1/health. Public open / inspect / replay take opaque bundleId values — not filesystem paths. See agent/README.md.

Repository map

Path	Role
MathEvidence/	Lean protocol types, encodings, checkers, tactics
adapters/	Untrusted backends (SymPy, Mathematica, and related)
agent/	AI-facing Agent API and SDKs
studio/	Notebook and editor surfaces
registry/	Capability declarations (all experimental today)
evidence/	Committed Evidence Bundles (schema v0.2 .cjson)
foundry/	Schemas and pipelines for certified tool-use episodes
benchmarks/	Conformance, adversarial, and real-world suites
docs/	Specs, status, trust model, getting started

Contribute

Contributions are welcome. Keep backends untrusted and Lean authoritative.

1. Read CONTRIBUTING.md and docs/STATUS.md.
2. Prefer a focused change with tests (positive, negative, and replay when relevant).
3. Run just check before opening a PR.
4. Do not flip capabilities to "stable" from a single PR — promotion follows a documented checklist with real human review.

Protocol-wide changes belong in an RFC under docs/rfcs/.

Documentation

Doc	Purpose
docs/README.md	Documentation landing
docs/getting-started/	Install, check, Agent API, first replay
docs/STATUS.md	Public-preview status
docs/security/KNOWN_TRUST_GAPS.md	Known limitations

Also: docs/SPEC_INDEX.md, docs/ROADMAP.md, docs/PROJECT_SPEC.md.

What to expect

• Everything in the registry is still experimental.
• A green local just check is useful feedback — not attested release CI or completed human review.
• Receipt crypto under dev/receipt-keys/ is dev-only, not production PKI.

When unsure, trust Lean’s checkers and the written limitations — not a backend status code.

---

License LICENSE (Apache-2.0) · Security SECURITY.md · Contributing CONTRIBUTING.md