LeanMarathon

LeanMarathon is an multi-agent harness system for turning a natural-language mathematical proof into fully-proven Lean 4 blueprint with parallel Codex agents. [Paper]

LeanMarathon manages GitHub repositories, sparse worktrees, Slurm jobs, Codex agent workspaces, runtime inputs, audit logs, and CI handoffs. User can operate the system through leanmarathon commands and a small local config file.

Deliveries

Target	Result
Erdős-Graham	ErdosGraham
Erdős #1196	Erdos1196
Erdős #164 & #1217	Prim

Repository Layout

Path	Purpose
src/leanmarathon/cli.py	User-facing CLI: init, auto, stage1 run, stage2 run, status, and doctor.
.scripts/create-worktree.sh	Creates sparse Git worktrees for agent branches.
.scripts/stage1_blueprint_loop.py	Slurm-backed Stage 1 Blueprinter / Target-Reviewer / Refiner loop.
.scripts/per_node_worker_loop.py	Slurm-backed Stage 2 Worker / Refiner loop.
.scripts/verify_blueprint.py	CI and local verifier for LeanArchitect blueprint files.
agents/Blueprinter/	Codex workspace template for initial blueprint generation.
agents/Target-Reviewer/	Codex workspace template for target review.
agents/Refiner/	Codex workspace template for blueprint and blocker repair.
agents/Worker/	Codex workspace template for one-node proof work.
mcp-servers/apply-patch/	Local MCP server for scoped patch application.
mcp-servers/dag-tracker/	Local MCP server for proof-DAG context queries.
workflows/verify-blueprint.yml	GitHub Actions template copied into target repos.
workflows/warmup-cache.yml	Optional cache warmup workflow copied into target repos.
config/local.example.toml	Local machine/cluster config template.
docs/params.md	CLI command argument reference.
tests/	Regression tests for prompt plumbing and verifier comment hygiene.

Agent Roles

Role	Branch pattern	Delivery
Blueprinter	blueprint/init	Creates the initial blueprint and delivers a CI-green PR merged into main.
Target-Reviewer	target-review/round-<n>	Reviews target statements and either exits cleanly or files a grouped issue.
Refiner	blueprint-refiner/round-<n> in Stage 1, refiner/round-<n> in Stage 2	Repairs open issues and delivers a CI-green PR merged into main.
Worker	round-<n>/<target_node>	Proves one dynamic leaf in Stage 2, or files a blocker issue.

Blueprinter, Refiner, and successful Worker jobs use Codex stop hooks. A stop hook keeps the agent alive until its PR is CI-green and merged. Target-Reviewer and blocked Workers may finish by filing an issue.

Default Codex start prompts are:

Role	Default prompt
Blueprinter	Begin from Phase 1
Target-Reviewer	Begin the work.
Refiner	Begin from Phase 1
Worker	Begin from Phase 1

Custom prompts can be provided at leanmarathon init with --blueprinter-prompt, --target-reviewer-prompt, --refiner-prompt, and --worker-prompt. Defaults are not written to prompt files; custom prompts are stored in the local target config and materialized inside each agent worktree so the agent doesn't lose the context after auto-compaction.

Requirements

LeanMarathon expects the following tool versions:

Tool	Expected version
Codex CLI	0.128.0
lean-lsp-mcp	0.26.2
lean-explore	1.2.1
github-mcp-server	0.32.0
git-mcp-server	2.10.5

LeanMarathon does not pin the Lean version. You must provide a Lean project root with compatible LeanArchitect containing:

lakefile.toml
lake-manifest.json
lean-toolchain

That Lean project root is also where local Lean tooling and .lake cache state are used. LeanMarathon worktrees are created under:

<lean_project_root>/.leanmarathon-worktrees/<owner>/<repo>/

Mandatory Python PDF imports:

Import	Use
pdfplumber	Default PDF text extraction for math papers.
fitz	PyMuPDF page inspection and fallback extraction.
pdfminer.high_level	Lower-level PDF text extraction.
pypdf	Pure-Python PDF fallback.
PyPDF2	Older PDF fallback.
pypdfium2	PDFium rendering and fallback extraction.

Optional numeric packages are auto-detected during leanmarathon init. LeanMarathon checks this known import list and exposes only installed rows to agents:

numpy scipy sympy numba torch mpmath pandas matplotlib networkx pulp ortools highspy pysat cvxpy osqp clarabel sklearn faiss

Install

Clone the system repo and install the Python CLI:

git clone <LeanMarathon repo URL> LeanMarathon
cd LeanMarathon
python3 -m venv .venv
. .venv/bin/activate
pip install -e .

Install the external MCP servers and Codex CLI according to your environment. LeanMarathon ships only the local apply-patch and dag-tracker MCP servers. The following MCP servers are external tools and must be installed separately:

• lean-lsp-mcp
• lean-explore
• github-mcp-server
• git-mcp-server

Then run:

leanmarathon doctor

doctor checks command availability, expected tool versions where possible, mandatory PDF imports, and optional numeric imports.

Local Machine Config

Create a local config file:

cp config/local.example.toml .leanmarathon.local.toml

Edit .leanmarathon.local.toml:

[paths]
venv_bin = "/absolute/path/to/LeanMarathon/.venv/bin"node_bin = "/absolute/path/to/node/bin"elan_bin = "/absolute/path/to/elan/bin"# Optional full overrides when the composed PATH is not enough.# agent_path = "/absolute/path/to/venv/bin:/absolute/path/to/node/bin:/absolute/path/to/elan/bin:/usr/local/bin:/usr/bin:/bin"# orchestrator_path = "/absolute/path/to/venv/bin:/absolute/path/to/node/bin:/absolute/path/to/elan/bin:/usr/local/bin:/usr/bin:/bin"
[lean]
project_root = "/absolute/path/to/lean-project"
[slurm]
cpu_account = ""gpu_account = ""gpu_partition = "gpu"gpu_gres = "gpu:lovelace_l40:1"mem_per_cpu = 3850

The default composed PATH is:

paths.venv_bin : paths.node_bin : paths.elan_bin : /usr/local/bin : /usr/bin : /bin

You can point LeanMarathon at a different local config with:

export LEANMARATHON_CONFIG=/absolute/path/to/local.toml

Environment variables override local config values:

Environment variable	Config field
LEANMARATHON_VENV_BIN	paths.venv_bin
LEANMARATHON_NODE_BIN	paths.node_bin
LEANMARATHON_ELAN_BIN	paths.elan_bin
LEANMARATHON_AGENT_PATH	paths.agent_path
LEANMARATHON_ORCH_PATH	paths.orchestrator_path
LEANMARATHON_LEAN_PROJECT_ROOT	lean.project_root
LEANMARATHON_SLURM_CPU_ACCOUNT	slurm.cpu_account
LEANMARATHON_SLURM_GPU_ACCOUNT	slurm.gpu_account
LEANMARATHON_SLURM_GPU_PARTITION	slurm.gpu_partition
LEANMARATHON_SLURM_GPU_GRES	slurm.gpu_gres
LEANMARATHON_SLURM_MEM_PER_CPU	slurm.mem_per_cpu

GitHub Auth

Authenticate with gh:

gh auth login

or export a LeanMarathon-specific token:

export LEANMARATHON_GITHUB_TOKEN=...

Required GitHub permissions:

Permission area	Needed for
Contents read/write	Push branches and initialize target repos.
Pull requests read/write	Open and merge agent PRs.
Issues read/write	File and close review/blocker issues.
Actions/workflows read/write	Install and trigger copied CI workflows.

Safety: Do not put GitHub tokens in .leanmarathon.local.toml, README files, agent configs, or committed target files. Generated Slurm jobs inherit a token from LEANMARATHON_GITHUB_TOKEN or from gh auth token; token values are not written into generated job scripts.

Initialize A Target Repo

Prepare:

Input	Meaning
problem_file	Canonical target statements.
proof_file	Natural-language proof source. This may be a file or a directory.
lean_project_root	Existing Lean project root containing Lake metadata and dependencies.

Create and initialize a private GitHub target repo:

leanmarathon init \
--owner MyGitHubName \
--repo MyTargetRepo \
--problem-file /absolute/path/to/problem.txt \
--proof-file /absolute/path/to/proof-source \
--lean-project-root /absolute/path/to/lean-project

If lean.project_root is already set in .leanmarathon.local.toml, the --lean-project-root argument can be omitted.

Useful initialization options:

leanmarathon init \
--owner MyGitHubName \
--repo MyTargetRepo \
--problem-file /absolute/path/to/problem.txt \
--proof-file /absolute/path/to/proof-source \
--public \
--lean-file LeanMarathon/Main.lean \
--auto-resource cpu \
--auto-cpus 1 \
--auto-time 48:00:00 \
--stage1-orchestrator-resource cpu \
--stage1-orchestrator-cpus 1 \
--stage1-orchestrator-time 48:00:00 \
--orchestrator-resource gpu \
--orchestrator-cpus 42 \
--orchestrator-time 48:00:00 \
--agent-resource gpu \
--agent-cpus 42 \
--agent-time 4:00:00 \
--batch-size 16 \
--max-review-rounds 20 \
--max-rounds 100

--orchestrator-* configures the Stage 2 Worker-loop orchestrator. Stage 1 has its own --stage1-orchestrator-* options. --auto-* configures the optional parent end-to-end Slurm job.

By default target repos are private. Use --public only when you want a public target repo.

What init Creates

In the target GitHub repo, LeanMarathon commits:

.gitignore
lakefile.toml
lake-manifest.json
lean-toolchain
LeanMarathon/Main.lean
.github/workflows/verify-blueprint.yml
.github/workflows/warmup-cache.yml
.scripts/verify_blueprint.py

Local runtime state is created in the LeanMarathon system repo:

Path	Meaning
.orchestrator-repos/<owner>/<repo>/	Local clone of the target repo used as the per-target orchestration root.
.leanmarathon-targets/<owner>/<repo>/config.toml	Local target config written by leanmarathon init.
.leanmarathon-targets/<owner>/<repo>/inputs/	Local copies of problem_file and proof_file.

Agent worktrees are created under the configured Lean project root:

<lean_project_root>/.leanmarathon-worktrees/<owner>/<repo>/

Per-run audit logs and Slurm scripts are written inside the local target clone:

.orchestrator-repos/<owner>/<repo>/.orchestrator-runs/

Codex session history for jobs is isolated under:

.orchestrator-repos/<owner>/<repo>/.codex-session-home/

After each agent job exits, the generated job script prunes the isolated Codex home, preserving Codex session .jsonl files. Worktree and feature-branch cleanup only runs when Codex exits successfully after a terminal delivery; failed or non-terminal jobs keep their worktrees and branches for debugging.

Run End To End

The command is:

leanmarathon auto --owner MyGitHubName --repo MyTargetRepo

By default, this submits one parent Slurm job. The parent job submits Stage 1, waits for Stage 1 to finish, submits Stage 2, and waits for Stage 2 to finish. To run the parent coordinator in the current terminal while still submitting Stage 1 and Stage 2 as Slurm jobs:

leanmarathon auto --owner MyGitHubName --repo MyTargetRepo --no-submit

Stage 1: Blueprint Generation And Review

Run Stage 1 directly:

leanmarathon stage1 run --owner MyGitHubName --repo MyTargetRepo

--no-submit runs the Stage 1 orchestrator in the current terminal instead of submitting the orchestrator itself to Slurm. Agent jobs are still Slurm jobs.

Stage 2: DAG-orchestrated Loop

Run Stage 2 directly:

leanmarathon stage2 run --owner MyGitHubName --repo MyTargetRepo

Slurm Resource Model

LeanMarathon uses Slurm for:

Job type	Config section	Default
Parent auto job	[hpc.auto]	CPU, 1 core, 48 hours
Stage 1 orchestrator	[hpc.stage1_orchestrator]	CPU, 1 core, 48 hours
Stage 2 orchestrator	[hpc.stage2_orchestrator]	GPU, 42 cores, 48 hours
Agent jobs	[hpc.agent]	GPU, 42 cores, 4 hours

The generated target config looks like:

[hpc.auto]
resource = "cpu"cpus = 1time = "48:00:00"
[hpc.stage1_orchestrator]
resource = "cpu"cpus = 1time = "48:00:00"
[hpc.stage2_orchestrator]
resource = "gpu"cpus = 42time = "48:00:00"
[hpc.agent]
resource = "gpu"cpus = 42time = "4:00:00"batch_size = 16

Resource mode gpu adds:

#SBATCH --partition=<slurm.gpu_partition>
#SBATCH --gres=<slurm.gpu_gres>

Resource mode cpu adds no GPU directives. If your cluster does not require Slurm accounts, leave cpu_account and gpu_account empty.

Agent job scripts export:

VERIFY_BLUEPRINT_LEAN_THREADS=<agent_cpus>
LEAN_LSP_THREADS=<agent_cpus>
DAG_TRACKER_LEAN_THREADS=<agent_cpus>
LEANMARATHON_TOTAL_MEM_MB=<agent_cpus * mem_per_cpu>

Runtime MCP Servers

LeanMarathon uses both external and local MCP servers.

External MCP servers must be installed by the user:

lean-lsp-mcp
lean-explore
github-mcp-server
git-mcp-server

Local MCP servers shipped in this repo:

Server	Purpose
mcp-servers/apply-patch/apply_patch_mcp.py	Structured patching without shell execution; optionally restricts Worker edits to one blueprint node.
mcp-servers/dag-tracker/dag_tracker_mcp.py	Queries parent nodes, child nodes, and global definitional context for one blueprint file.

The orchestrators patch each copied agent .codex/config.toml so MCP servers point at the concrete worktree, Lean file, Lean project root, and target node.

Monitor A Run

Show target status:

leanmarathon status --owner MyGitHubName --repo MyTargetRepo

This prints the local target root, open GitHub issues, open PRs, and the latest local run directory.

Important run files for observability:

Path pattern	Meaning
.orchestrator-runs/auto-*/auto.out and auto.err	Parent end-to-end coordinator logs.
.orchestrator-runs/stage1-*/stage1.out and stage1.err	Stage 1 orchestrator logs.
.orchestrator-runs/worker-loop-*/orchestrator.out and orchestrator.err	Stage 2 orchestrator logs.
.orchestrator-runs/**/jobs/**/job.out and job.err	Individual agent Slurm logs.
.orchestrator-runs/**/stage1_result.json	Stage 1 machine-readable result.
.orchestrator-runs/**/result.json	Stage 2 machine-readable result.
.orchestrator-runs/**/audit.jsonl or stage1_audit.jsonl	Round-by-round audit entries.

Resume and Cleanup

For normal resume:

leanmarathon stage2 run --owner MyGitHubName --repo MyTargetRepo

Stage 2 can auto-resume by default. If a previous run ended after Workers filed issues but before a Refiner ran, the next leanmarathon stage2 run resumes that same round and dispatches the Refiner first. Otherwise it starts at the next recorded round.

Troubleshooting

Run:

leanmarathon doctor
leanmarathon doctor --owner MyGitHubName --repo MyTargetRepo

Common issues:

Symptom	Likely cause and fix
GitHub repo setup requires gh on the configured PATH	Put gh on paths.venv_bin, paths.node_bin, paths.elan_bin, or one of the optional PATH overrides.
Resource not accessible by personal access token	The token lacks contents, PR, issue, actions, or workflow permissions. Prefer LEANMARATHON_GITHUB_TOKEN or refresh gh auth login.
No workflow run appears	The PR did not touch LeanMarathon/**/*.lean, workflow permissions are missing, or GitHub Actions is delayed.
CI says only .scripts/verify_blueprint.py is missing	The target repo was not initialized by current leanmarathon init; reinitialize or copy the trusted verifier into target main.
Lean LSP cannot find a project	Check lean.project_root, paths.elan_bin, and that worktrees are under <lean_project_root>/.leanmarathon-worktrees/.
DAG extraction times out	Increase orchestrator CPU threads/time or reduce heavy Lean proofs; timeouts exit instead of filing a compilation issue.