mathlib-quality

A Claude Code skill plugin for developing, proving, cleaning up, and bringing Lean 4 code up to mathlib standards.

Built on 14,000+ real mathlib PR review comments with 7,273 before/after code suggestions, extracted into concrete golfing rules and quality principles.

What It Does

Develop New Mathematics — Plan with /develop, then Execute with /beastmode

The development workflow is split into planning and execution to prevent the "agent reconsiders the whole approach mid-proof" failure mode. /develop does the strategic thinking; /beastmode does the tactical implementation; neither does the other's job.

/develop — planning only.

• Comprehensive plan from your references; exhaustive mathlib search; API design for every new declaration.
• Detailed self-contained tickets. Every proof/definition ticket contains the full Lean Statement, a numbered Proof Sketch citing sources, the Mathlib lemmas needed (verified to exist), the Sources with bibliographic info, and the Generality decision. Detailed enough that no replanning is needed once execution starts.
• Algorithmic cleanup-cadence: every 3 proof tickets per file → cleanup ticket; per-file finals; pre-milestone /cleanup-all; final-of-everything cleanup. The cadence is verified at planning time and re-checked at every resume audit.
• Resume & takeover modes: --continue audits the ticket board against the current code and proposes updates (including missing cleanup tickets); --takeover creates a plan for an existing project. Both end with a hand-off to /beastmode.
• No execution. Once the board is approved, /develop stops.

/beastmode — marathon execution. Stops at nothing — but stays on-target.

• Pick a ticket, finish the goal. No matter how deep the path goes. When a sub-step needs a missing lemma, missing dependency, or sub-result that isn't on the board, the worker spawns a sub-ticket in /develop's ticket-template format and immediately works it. When the parent's sketch turns out to be wrong as a strategy, the worker invokes /develop --continue to replan inline and keeps going.
• On-target vigilance, continuously. Before each sub-ticket and step, the worker confirms: serves the plan's main goal? stays in the project's mathematical area? a refinement, not a divergence? Vigilance is for on-target work, not against it.
• Scope growth that stays on-target is great news. A "two lemmas" step turning out to need ten is more mathematics captured — exactly the point of the marathon. The harder the work, the more energy goes in (Super Saiyan ethos: the stronger the opponent, the stronger you get).
• No recursion cap, no time budget. "It's late", "this is taking a while", "we're 5 sub-tickets deep", "let me try a different approach" — none of these are legitimate stops.
• Only legitimate stops: DONE / SCOPE-DEFINITION ERROR (statement actually wrong) / OFF-TRACK (drift onto material genuinely outside the project's mathematical area, with concrete evidence) / BROKEN BASELINE (lake build broken on entry).
• Quality enforced throughout — no sorry, no new axioms (#print axioms checked), maximum generality, gates run on the diff before marking the ticket done.

Clean Up Existing Code (/cleanup)

Methodical 8-phase workflow for any Lean file. Replaces what used to be three commands (/check-style, /check-mathlib, plus the original /cleanup):

• Phase 0 — Doctor: pre-flight lake build baseline check; aborts if the project doesn't currently compile (we can't tell what we broke without a clean baseline)
• Phase 2 — Style audit: full numbered punch-list; what was the standalone /check-style
• Phase 3 — File-level fixes: copyright + module docstring (CREATED if missing) + imports + subsection-divider strip + set_option removal + batched mechanical replacements
• Phase 4 — Per-declaration deep cleanup: one worker per decl; 18-item audit with required status blocks for golf rules (1.1 → 3.7), the five-method mathlib search (formerly /check-mathlib), and inline /generalise mechanical pass with literature search for public decls
• Phase 5 — Refactoring: cross-declaration items (renames, junk-def inlining, mathlib replacements, big-change generalisations escalated to standalone /generalise)
• Phase 6 — Final verification: file-level gates (definition_protected, theorem_statement_protected, lake_build_file, cumulative_no_unintended_breakage) — borrowed from shouyi
• One agent per declaration, deep focus on shortest proof; 60+ rules from golfing-rules.md and proof-patterns.md applied systematically (data-driven from 7,273 PR suggestions)

Additional Tools

• /project-status — chat-only mathematical status report. Reads the project's .lean files (plus plan.md / tickets.md if present) and answers four questions in mathematical English: what result is the worker on, what (if anything) is blocked and what is mathematically missing, how does the current work connect to the overall goal, and how far along is the whole project. Three-tier progress — code-level coverage (declarations sorry-free), main-goal chain coverage (only the dependency closure of the main result), and distance-to-unconditional (parametric hypotheses on the main goal still to discharge). Unicode math only, no LaTeX. Read-only — no server, no browser.
• /generalise — weaken assumptions on a single lemma/def: typeclass-hierarchy walk, drop-test, point-localise, strict→weak, plus mandatory literature search; auto-applies small safe changes, presents big changes as a numbered approval menu (also runs inline as part of /cleanup Phase 4)
• /decompose-proof — break proofs >30 lines into focused helper lemmas (with mandatory user approval gate before dispatch)
• /expert-review — produce a self-contained mathematical brief (REVIEW_BRIEF.md) for an external reviewer with no repo access; pure math, no Lean, no file paths; then in Mode 2 (--reply) integrate the reviewer's response into ticket-board updates
• /fix-pr-feedback — fetch every PR comment, fix locally, stop for explicit user approval before pushing, then watch CI to completion (gh pr checks --watch runs in background as the wake-timer). Every commit and any PR-description update follows binding conventions: short imperative subject, concrete bullet body, dependencies surfaced via a Depends on #1234 line, Claude co-author footer.
• /bump-mathlib — bump mathlib version and fix the resulting breakage; documents recurring patterns from upstream evolution (Splits binary→unary refactor, IsX field-name normalisation, etc.)
• /pre-submit — final pre-PR checklist
• /overview — project-wide declaration inventory: every def/lemma/theorem with descriptions, dependencies, and consolidation analysis
• /split-file — split files >1000 lines (with mandatory user approval gate)

Installation

Option 1: Claude Code Plugin

/plugin marketplace add CBirkbeck/mathlib-quality
/plugin install mathlib-quality

Also install the lean4-skills plugin, which provides the Lean 4 theorem proving workflows that mathlib-quality builds on:

/plugin marketplace add cameronfreer/lean4-skills
/plugin install lean4

Option 2: Local Clone

git clone https://github.com/CBirkbeck/mathlib-quality.git

Then in Claude Code:

/plugin marketplace add /path/to/mathlib-quality

Lean LSP MCP Server (Highly Recommended)

Nearly all commands (/develop, /cleanup, /decompose-proof, etc.) depend on the lean-lsp-mcp server for sub-second feedback instead of 30+ second lake build cycles. It provides tools like lean_goal, lean_diagnostic_messages, lean_multi_attempt, lean_loogle, and more.

Prerequisites:

• uv (Python package manager)
• A Lean 4 project with lakefile.lean
• Run lake build once in your project before starting (the LSP server needs oleans)

Setup (run from your Lean project root):

# User-scoped (recommended) — available in all your projects
claude mcp add --transport stdio --scope user lean-lsp -- uvx lean-lsp-mcp

# Or project-scoped — shared via .mcp.json
claude mcp add --transport stdio --scope project lean-lsp -- uvx lean-lsp-mcp

User-scoped (--scope user) is recommended — it is more reliable for keeping MCP tools visible inside subagents.

Restart Claude Code after adding. Verify by checking that tools like lean_goal and lean_diagnostic_messages appear.

Optional: RAG MCP Server

The plugin includes a searchable index of PR review examples. To enable:

/setup-rag

Optional: ChatGPT MCP Server

Get mathematical second opinions from ChatGPT during Lean 4 work. After setup, Claude Code gains an ask_chatgpt_math tool for verifying claims, finding Mathlib API hints, or getting unstuck on formalization problems.

Requirements:

• ChatGPT desktop app (provides the Codex CLI binary)
• ChatGPT Plus/Pro subscription
• Node.js >= 18

Run the setup command and it will walk you through everything:

/setup-chatgpt

The command locates the Codex CLI, creates an MCP server at ~/.claude/mcp-servers/chatgpt-math/, installs dependencies, and adds the server to your project's .mcp.json. Restart Claude Code after setup to activate the new tool.

Commands

Command	Description
/develop	Planning only. Mathlib search, API design, detailed tickets (Statement + Proof Sketch + Mathlib lemmas + Sources + Generality per ticket). Stops after approval.
/beastmode	Marathon execution. Stops at nothing — but stays on-target. Pick a ticket and finish the goal — spawn sub-tickets in /develop's format for missing lemmas, replan via /develop --continue for wrong strategies, no recursion cap, no time budget. Super Saiyan ethos: scope growth that stays on-target is great news, not a stop signal. Multi-session work is the target, not an exit. Only stops: DONE / SCOPE-DEFINITION ERROR / OFF-TRACK (genuine, with concrete evidence) / BROKEN BASELINE.
/cleanup	Style audit + cleanup + golf (whole file or single declaration). 9-phase methodical workflow; absorbed /check-style (Phase 2 audit) and /check-mathlib (Phase 4 item 13: five-method search-status block + six strict mathlib-replacement rules).
/cleanup-all	Orchestrator-worker marathon. Main session dispatches batched Agent calls with tight prompts (working dir + branch + build + file list + target); workers do all file reading, LSP, edits, and build verification in fresh contexts. Between dispatches the orchestrator emits a one-line scoreboard, nothing else. The pattern that sustained a real 28-day, 9000-message, 395-dispatch cleanup session.
/project-status	Chat-only mathematical status: what's the worker on, what's blocked + missing, how it connects to the goal, how far along. Three-tier progress (code-level / main-goal chain / parametric-hypotheses discharged). Unicode math, no LaTeX.
/overview	Project-wide declaration inventory: every def/lemma/theorem with descriptions, dependencies, consolidation analysis
/expert-review	Two-mode external review: produce a self-contained math brief (REVIEW_BRIEF.md), wait for the reviewer's response, then integrate their guidance into the ticket board
/generalise	Weaken assumptions on a lemma or definition: mechanical weakenings + literature search; auto-apply small safe changes, propose big changes as a numbered menu
/decompose-proof	Break long proofs into helper lemmas
/split-file	Split files >1000 lines (with approval gate)
/pre-submit	Pre-PR submission checklist
/fix-pr-feedback	Fetch PR comments → fix → STOP for approval → push → watch CI. Every commit and PR-description update follows binding conventions (short imperative subject, concrete bullet body, Depends on line, Claude co-author footer).
/bump-mathlib	Bump mathlib version and fix breakage
/teach	Record a project-specific pattern or convention
/contribute	Push local learnings back as a PR to this repo
/setup-rag	Configure the RAG MCP server
/setup-chatgpt	Configure ChatGPT MCP server for mathematical second opinions

Usage

Developing New Mathematics

# Plan
/develop                   # Plan a new development (creates the ticket board)
/develop --continue        # Audit ticket board against the code, propose updates
/develop --status          # Show current ticket board
/develop --takeover        # Plan a takeover of an existing project

# Execute
/beastmode                 # Pick the next available ticket and work it to completion
/beastmode --ticket T042   # Specific ticket
/beastmode --resume        # Resume an in_progress ticket from its progress notes

# Check status between sessions
/project-status            # Chat report: what's the worker on, what's blocked, how far from the goal

# Finish
/pre-submit                # Final-review checklist after all tickets are done

How /develop works (planning):

1. Gather context — goal, references, scope.
2. Study references — read user-provided papers / books to extract the canonical statements and proof outlines that will populate tickets.
3. Search mathlib exhaustively for existing relevant definitions and lemmas.
4. Design the API — maximally general typeclasses, namespace conventions, what to define vs. import.
5. Write the plan in .mathlib-quality/plan.md.
6. Create detailed tickets — every ticket gets full Statement, Proof Sketch, Mathlib lemmas needed, Sources, Generality decision.
7. (Optional) ChatGPT plan validation if MCP available.
8. User approval. After approval, /develop stops.

How /beastmode works (execution):

1. Pick — auto-pick the next ticket whose dependencies are done, or honour --ticket TXXX.
2. Read the ticket fully. If any required field (Statement / Proof Sketch / Mathlib lemmas / Sources / Generality) is missing, refuse to start and ask the user to re-run /develop to complete the ticket.
3. Pre-work checks — dependencies actually done; lake build baseline clean.
4. State the declaration verbatim from the ticket's Statement field.
5. Prove by walking the proof sketch step by step; verify each cited mathlib lemma exists; use lean_multi_attempt aggressively; checkpoint progress in the ticket as you go.
6. Verify — diagnostics clean, no sorry, axiom check, lake build clean.
7. Gates on the diff (definition_protected, theorem_statement_protected, etc.).
8. Mark done + report. If a hard-stop condition fires instead, the report names which step failed, what was tried, and a concrete replanning suggestion.

When all tickets are done, run /pre-submit for the final-review checklist (no sorry anywhere, no new axioms, full project build clean, etc.).

Cleaning Up Code

/cleanup MyFile.lean                # Clean entire file
/cleanup MyFile.lean theorem_name   # Clean one declaration
/cleanup-all                        # Clean every file in project

How /cleanup works (9 phases, methodical, no skipping):

0. Doctor — pre-flight: lake exe cache get, lake build (must pass — without a clean baseline we can't tell what breakage we introduced), LSP responsive on the target file. Aborts if the baseline is broken.
1. Prepare — read the file, run lean_diagnostic_messages, read the five reference docs (golfing-rules, proof-patterns, mathlib-search, generalisation-patterns, cleanup-gates), build the declaration list.
2. Style audit — complete numbered punch-list (file-level + linter findings + per-declaration light scan). No fixes yet. Replaces what used to be /check-style.
3. File-level fixes — copyright, module docstring (CREATED if missing), imports, subsection dividers, file-level set_option, batch mechanical replacements (λ→fun, $→<|, push_neg→push Not).
4. Per-declaration deep cleanup — one dedicated agent per declaration. The worker reads the reference docs, runs the 18-item audit with required status blocks for: every golfing rule (1.1 → 3.7), the five-method mathlib search (with the six strict mathlib-replacement rules — replaces /check-mathlib), the inline mechanical generalisation pass (catalogue-driven typeclass-hierarchy walk, drop-test, pointwise / strict→weak), and (for public decls) a literature search. Then runs the diff gates on the worker's edits before completing.
5. Refactoring — cross-declaration items from Phase 4 worker reports: renames, junk-def inlining, mathlib replacements, big-change generalisations escalated to standalone /generalise (which has the user-approval gate on big changes).
6. Final verification — file-level diff gates (lake_build_file, lake_build, definition_protected, theorem_statement_protected, cumulative_no_unintended_breakage). Untraceable signature changes are gate failures; only continues if Phase 6 is pass. 6½. Simplify pass — hand off to the built-in /simplify skill (provided by Claude Code) for a holistic review. Where /cleanup is checklist-driven, /simplify is holistic — it spots duplicated proof skeletons across the file, cross-cutting issues the per-declaration workers missed, and quality issues that don't match any specific rule. If /simplify makes changes, the gates from Phase 6 are re-run on the new state. Required artifact: simplify-pass status block.
7. Report — one consolidated report including the Phase-0 baseline, the audit punch-list, per-declaration before/after, refactoring done, gate-status table, and the simplify-pass outcome.

No-skipping enforcement. /cleanup's anti-skip defence sits on four mechanisms: required artifacts (status blocks the agent must emit — golf-rule status, mathlib search-status, generalisation status, gate status, simplify status; missing or blank cells = step skipped), verification gates between phases (lake build baseline, diagnostics-clean), diff gates on edits (definition_protected, theorem_statement_protected — catches out-of-scope edits), and user-approval pauses for high-blast-radius actions. The Phase-7 report's required-section list lets a missing artifact fail the report.

Preparing a PR

/cleanup MyFile.lean            # Audit + fix + golf (one command)
/pre-submit MyFile.lean         # Final checklist

Handling PR Feedback

/fix-pr-feedback 1234              # Process feedback from mathlib PR #1234
/fix-pr-feedback --comments "..."  # Or paste specific comments

How /fix-pr-feedback works (8 phases, push-gated):

1. Fetch — pull every review comment, issue comment, and PR-review summary via gh api.
2. Triage — numbered punch-list with severity (🔴 must-fix, 🟡 should-fix, 🟢 question, ⚪ resolved) and category (golf / style / naming / api-design / correctness / …).
3. Implement — fix each item in priority order (correctness → naming → golf → style → docs → questions); for proof rewrites, dispatches /cleanup-Phase-4-style workers.
4. Coverage check — re-fetches comments and cross-references by id; any comment not in the action log is treated as a defect and addressed before continuing.
5. STOP for user approval — prints the full report (changes, deferred items with reasons, drafted replies for the reviewer) and waits for explicit OK to push. No silent push.
6. Push + watch CI — once approved, git push then gh pr checks --watch in the background. The runtime auto-notifies when checks finish — that's the wake-timer.
7. CI follow-up — if CI fails, diagnose, fix, return to Phase 5 (still no push without approval).
8. Final report + learnings — once green, summarise and write learnings.

Design Philosophy: Methodical Phases + Required Artifacts

The recent rewrites of /cleanup, /fix-pr-feedback, /develop, /beastmode, /project-status, /expert-review, /generalise, /decompose-proof, /split-file, /integrate-learnings, /bump-mathlib, and /overview all follow a single pattern:

1. Multi-step procedures with explicit phase numbers. A workflow that says "do X, then Y, then Z" silently drops Y when the agent gets tired. A workflow with PHASE 1 … PHASE 8 makes phase-skipping visible.
2. Required artifacts. Each phase produces a structured output — a punch-list, a status block, a gate-status table, a per-hypothesis classification table. The artifact is the proof the phase actually ran. Skipping a step is detectable in the missing or malformed artifact.
3. No silent skipping. Every rule, every search method, every hypothesis, every comment, every reviewer point gets explicit status: applied, tried-and-failed, n/a: <reason>. Blank entries are defects. Recent example: /cleanup's Phase-4 worker emits a per-rule status line for every entry in golfing-rules.md (sections 1.1 through 3.7), so a worker that silently skipped automation upgrades produces a report with missing rules.
4. Verification gates between phases. A phase doesn't complete until its check passes. The /cleanup Phase-4 worker can't move past Step 5 without lean_diagnostic_messages being clean and the diff gates (definition-protection, theorem-statement-protection, lake-build-file) passing. The Phase-0 doctor blocks the whole workflow if the project doesn't currently build.
5. User-approval pauses for high-blast-radius actions. Pushing to a remote (/fix-pr-feedback Phase 5), executing a file split (/split-file), dispatching decomposition (/decompose-proof), applying big-change generalisations (/generalise Phase 8), and integrating ambiguous community learnings (/integrate-learnings 5c) all stop at an explicit AWAITING USER APPROVAL line and wait. No silent push, no silent overwrite, no "while we're here".
6. Cleanup discipline as algorithm, not vibe. /develop's cleanup-cadence is "every 3 proof tickets per file → cleanup ticket; finals per file; pre-milestone cleanup-all; final cleanup-all", checked at every ticket pickup and every replanning. "Insert a cleanup every 3-5 proof tickets" was getting skipped; an algorithm with a verify-count check before saving the board doesn't.
7. Diff-level gating, not just LSP diagnostics. Borrowed from shouyi: every AI-generated edit gets diff-checked against gates that catch categorical mistakes (touched a def line that wasn't supposed to change; modified a theorem statement during what was supposed to be a proof-only golf). LSP diagnostics catch type errors; gates catch policy violations.

The throughline: enforcement happens through artifacts the agent must emit, not through guidelines the agent should remember.

Key Rules (from 14,000+ PR reviews)

The Cardinal Rule: Terminal vs Nonterminal simp

• Terminal simp must NOT be squeezed -- leave as simp or simp [lemmas]
• Nonterminal simp MUST be squeezed to simp only [...]
• This is the #1 most enforced rule in mathlib reviews (282+ comments)

Tactic Priority (try in order)

Priority	Tactic	Use for
1	grind	General closing (subsumes many chains)
2	simp / simpa	Simplification (DON'T squeeze terminal)
3	aesop	Logic, membership, set goals
4	fun_prop	Continuity, differentiability, measurability
5	positivity	0 < x, 0 <= x goals
6	gcongr	Inequality congruence
7	lia	Nat/Int arithmetic (preferred over omega)
8	norm_num	Numeric computation
9	ring / field_simp; ring	Polynomial/field equalities

Top Golfing Patterns

Before	After
:= by exact term	:= term
rw [h]; exact e	rwa [h]
simp [...]; exact h	simpa [...] using h
constructor; exact a; exact b	exact <a, b>
apply f; exact h	exact f h
by_contra h; push_neg at h	by_contra! h
fun x => f x	f (eta-reduce)
have h := x; exact h	exact x

Style Rules

• Line length: 100 chars max
• Proof length: 50 lines max (decompose if longer)
• by at end of preceding line, never on its own line
• No comments inside proofs
• No sorry in committed code
• No new axioms

Naming Conventions

Declaration	Convention	Example
lemma/theorem	snake_case	continuous_of_bounded
def	lowerCamelCase	cauchyPrincipalValue
structure	UpperCamelCase	ModularForm

Pattern: conclusion_of_hypothesis (e.g., norm_le_of_mem_ball)

Data

Built from scraping 3,772 merged mathlib4 PRs:

Data	Count
Reviewer feedback items	14,063
Before/after code suggestions	7,273
RAG indexed examples	5,752
Proof golf examples	6,782
Style feedback items	2,390
API design feedback	3,566

All data is privacy-preserving -- only technical content is collected, no personal information.

Project Structure

mathlib-quality/
├── commands/                    # Slash command implementations
│   ├── develop.md               # Planning-only: mathlib search, API design, detailed tickets
│   ├── beastmode.md            # Marathon execution: spawn sub-tickets, replan, stop at nothing
│   ├── cleanup.md               # Style audit + fix + golf (8-phase; absorbed /check-style + /check-mathlib)
│   ├── cleanup-all.md           # Project-wide cleanup (one /cleanup per file)
│   ├── decompose-proof.md       # Break long proofs into helper lemmas (with approval gate)
│   ├── expert-review.md         # Two-mode external review: brief → wait → integrate reply into tickets
│   ├── generalise.md            # Weaken hypotheses; mechanical pass + literature search; user approval for big changes
│   ├── split-file.md            # Split files >1000 lines (with approval gate)
│   ├── overview.md              # Per-declaration project inventory
│   ├── project-status.md        # Chat-only mathematical status: three-tier progress, on-target / blockers
│   ├── pre-submit.md            # Final pre-PR checklist
│   ├── fix-pr-feedback.md       # 8 phases: fetch → fix → coverage check → STOP → push → watch CI
│   ├── bump-mathlib.md          # Bump mathlib + fix breakage (cache verification gate)
│   ├── teach.md                 # Record a project-specific pattern
│   ├── contribute.md            # Push local learnings back as a PR
│   ├── integrate-learnings.md   # (maintainers) merge contributed learnings into refs + RAG
│   ├── setup-rag.md             # Configure the RAG MCP server
│   └── setup-chatgpt.md         # Configure the ChatGPT MCP server
├── skills/mathlib-quality/
│   ├── SKILL.md                 # Main skill definition
│   └── references/              # Authoritative reference docs read by workers:
│       ├── style-rules.md           # File structure, formatting, deprecation
│       ├── naming-conventions.md    # snake_case/camelCase/UpperCamelCase + symbol dictionary
│       ├── golfing-rules.md         # Phase 1/2/3 rules (instant wins, automation, cleanup)
│       ├── proof-patterns.md        # Data-driven patterns from 7,273 PR suggestions
│       ├── mathlib-search.md        # Five-method exhaustive search + six strict rules
│       ├── generalisation-patterns.md  # Typeclass-weakening catalogue
│       ├── cleanup-gates.md         # Diff gates for /cleanup (borrowed from shouyi)
│       ├── pr-feedback-examples.md  # Curated review-category examples
│       └── linter-checks.md         # Mathlib's built-in linters
├── mcp_server/
│   └── mathlib_rag.py           # MCP server for RAG queries over the PR-feedback index
├── scripts/                     # Scraping, analysis, query, and merge tools
└── data/
    ├── pr_feedback/             # RAG indexes (built from 3,772 merged PRs)
    └── community_learnings/     # /contribute submissions; archived/ once merged

Acknowledgements

This plugin builds on tools, ideas, and writing from across the Lean / mathlib community. In particular:

Skill design and tooling

• frenzymath/shouyi — the gates pattern that /cleanup uses in Phase 0 (pre-flight lake build doctor), Phase 4 (per-worker diff gates), and Phase 6 (file-level cumulative gates). Shouyi treats every AI-generated edit as a diff that must pass programmatic gates (definition_protected, theorem_statement_protected, lake_build_file, docstring_only_changes) before acceptance — a structurally more robust pattern than "edit, then diagnose afterwards". See references/cleanup-gates.md.
• cameronfreer/lean4-skills — multi-cycle proving approach and proof-golfing methodology, plus the Lean 4 development workflows that /develop builds on.
• oOo0oOo/lean-lsp-mcp — the MCP server that gives every command sub-second feedback (lean_goal, lean_diagnostic_messages, lean_multi_attempt, lean_loogle, etc.) instead of 30+ second lake build cycles. Nearly every command depends on it.
• delta-lab-ai/Lean-Finder — AI-powered mathlib search supporting both type signatures and natural-language queries; method (A) of the five-method search-status block in /cleanup's Phase-4 MATHLIB audit. See references/mathlib-search.md.
• kim-em/botbaki — style conventions and formatting guidelines that informed early versions of style-rules.md.

Authoritative content sources

• leanprover-community style guide — the canonical reference for references/style-rules.md. All file-structure rules, formatting conventions, indentation, line-length, and tactic-mode style come from here.
• leanprover-community naming guide — the canonical reference for references/naming-conventions.md (snake_case for lemmas, lowerCamelCase for defs, the symbol dictionary, the conclusion_of_hypothesis pattern, etc.).
• leanprover-community PR review guide — informs the review-categories structure in references/pr-feedback-examples.md.

Data

• leanprover-community/mathlib4 — 3,772 merged PRs scraped for 14,063 reviewer-feedback items and 7,273 before/after code suggestions. Privacy-preserving: only public, technical content collected.
• Community contributors to this repo via /contribute: each archived JSONL in data/community_learnings/archived/ represents lessons learned by other Lean users on real PRs (Eisenstein series cleanup, Hecke algebra formalisation, modular forms PR reviews, version-bump breakage, file-deprecation conventions). These feed both the RAG index and — when consensus emerges — the reference docs.

Contributing

1. Fork the repository
2. Make changes
3. Test locally: /plugin marketplace add /path/to/your/fork
4. Submit a PR

License

MIT License -- see LICENSE