MLML

Operational pipeline to start, monitor, STOP, and recover the MathBench missing-lemma loop running in multi-node fleet mode on the MBZUAI cluster (watcher + slurmx fleet REPLs + login-node RPC host + serial adjudication + phase-2 import reconciliation). Use when launching/resuming the fleet run, stopping it cleanly, recovering after a crash, or applying the hard-won operational rules (correct kill sequence, git safety on the shared checkout, shell/conda/timeout fixes, re-collection prerequisite). For the single-machine AoA×PutnamBench eval use `aoa-putnam-eval` instead; for the design rationale of the loop see `MISSING_LEMMA_LOOP.md`.

How to refresh the local semantic embedding database (~1.5 GB of LMDB at ~/.cache/Isabelle_Semantic_Embedding). The development channel is the Hugging Face Hub tarball via manage_data.py (get/update). End users instead pull it anonymously from Cloudflare R2 with `semantics_manage.py pull`. Use when setting up or refreshing the semantic DB on a machine, or when deformalizations / vector stores are stale or missing. Do NOT run R2 `push` — it overwrites the shared remote and is a human-only action.

How to repackage/upload and download/unpack the Isabelle + paired AFP distribution, published together as contrib/Isabelle2025-2_and_afp-2026-05-13.tar.zst on the Hugging Face Hub (via manage_data.py update/get). Use when publishing a rebuilt Isabelle+AFP tarball (after isabelle scala_build, patches, etc.) or installing/refreshing the distribution on another machine.

How to read Isabelle introduction and elimination rules

Playbook for adding a new import to MathBench_ProverBase and reconciling any syntax conflicts (constant/type short-name resolution and notation) so that PutnamBench problems still parse to identical goal terms. Use when adding/changing imports of the MathBench_Prover session, or when investigating MathBench-vs-PutnamBench environment divergences.

How to read constants and theorems generated by Isabelle datatype and codatatype definitions

Essential reference for all Isabelle/ML development — system library, data structures, exception handling, and coding patterns. Load this skill whenever writing or modifying Isabelle/ML code.

Isabelle/ML coding style guide and conventions based on official implementation documentation

Techniques for developing proof tools in Isabelle, including understanding HHF (Hereditary Harrop Formula) proof state representation

How to read constants and theorems generated by Isabelle record definitions

How to write Isabelle/Scala plugins (Scala.Fun) that ML can call via PIDE protocol