erdos-prove — for Claude Code erdos-prove, erdos-banger, community, for Claude Code, ide skills, combinatorics, erdos-problems, formal-verification, mathematics, number-theory

v1.0.0

이 스킬 정보

적합한 상황: Ideal for AI agents that need erdos problem proving workflow. 현지화된 요약: This workflow helps you prove Erdos problems in Lean 4 using your Claude Code/Codex subscription instead of paid API calls. It covers cli, combinatorics, erdos-problems workflows.

기능

Erdos Problem Proving Workflow
Target Problem: $ARGUMENTS
Tip: If no problem ID provided, check CANDIDATES.md for the current focus problem (see Decision
┌─────────────────────────────────────────────────────────────────┐
│ COST-FREE PROVING WORKFLOW │

# Core Topics

The-Obstacle-Is-The-Way The-Obstacle-Is-The-Way
[4]
[2]
Updated: 2/1/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
52
Canonical Locale
en
Detected Body Locale
en

적합한 상황: Ideal for AI agents that need erdos problem proving workflow. 현지화된 요약: This workflow helps you prove Erdos problems in Lean 4 using your Claude Code/Codex subscription instead of paid API calls. It covers cli, combinatorics, erdos-problems workflows.

이 스킬을 사용하는 이유

추천 설명: erdos-prove helps agents erdos problem proving workflow. This workflow helps you prove Erdos problems in Lean 4 using your Claude Code/Codex subscription instead of paid API calls.

최적의 용도

적합한 상황: Ideal for AI agents that need erdos problem proving workflow.

실행 가능한 사용 사례 for erdos-prove

사용 사례: Applying Erdos Problem Proving Workflow
사용 사례: Applying Target Problem: $ARGUMENTS
사용 사례: Applying Tip: If no problem ID provided, check CANDIDATES.md for the current focus problem (see Decision

! 보안 및 제한 사항

  • 제한 사항: Optional API sources (rate-limited, mostly free):
  • 제한 사항: uv run erdos refs s2 citations <doi - Semantic Scholar (rate-limited)
  • 제한 사항: Requires repository-specific context from the skill documentation

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is erdos-prove?

적합한 상황: Ideal for AI agents that need erdos problem proving workflow. 현지화된 요약: This workflow helps you prove Erdos problems in Lean 4 using your Claude Code/Codex subscription instead of paid API calls. It covers cli, combinatorics, erdos-problems workflows.

How do I install erdos-prove?

Run the command: npx killer-skills add The-Obstacle-Is-The-Way/erdos-banger/erdos-prove. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for erdos-prove?

Key use cases include: 사용 사례: Applying Erdos Problem Proving Workflow, 사용 사례: Applying Target Problem: $ARGUMENTS, 사용 사례: Applying Tip: If no problem ID provided, check CANDIDATES.md for the current focus problem (see Decision.

Which IDEs are compatible with erdos-prove?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for erdos-prove?

제한 사항: Optional API sources (rate-limited, mostly free):. 제한 사항: uv run erdos refs s2 citations <doi - Semantic Scholar (rate-limited). 제한 사항: Requires repository-specific context from the skill documentation.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add The-Obstacle-Is-The-Way/erdos-banger/erdos-prove. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use erdos-prove immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

erdos-prove

Install erdos-prove, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Erdos Problem Proving Workflow

Target Problem: $ARGUMENTS

Tip: If no problem ID provided, check CANDIDATES.md for the current focus problem (see Decision Log).

This workflow helps you prove Erdos problems in Lean 4 using your Claude Code/Codex subscription instead of paid API calls.

Overview

text
1┌─────────────────────────────────────────────────────────────────┐ 2│ COST-FREE PROVING WORKFLOW │ 3├─────────────────────────────────────────────────────────────────┤ 4│ 1. Understand → Read problem statement (FREE) │ 5│ 2. Research → Gather literature context (FREE) │ 6│ 3. Formalize → Generate Lean skeleton (FREE) │ 7│ 4. Prove → Work with Claude Code (SUB) │ 8│ 5. Verify → Check Lean compilation (FREE) │ 9│ 6. Iterate → Fix errors with Claude Code (SUB) │ 10└─────────────────────────────────────────────────────────────────┘

Step 1: Understand the Problem

First, let me read the problem statement and understand what we're trying to prove.

Action: I will read the problem details using:

  • data/problems_enriched.yaml (if present) or src/erdos/data/problems_enriched.yaml (built-in sample dataset)
  • erdos show $ARGUMENTS output for formatted display

Questions to answer:

  • What is the mathematical statement?
  • What is the current status (open, partially solved)?
  • Are there any known partial results?

Step 2: Research Existing Literature

Gather context from existing references without making API calls.

Local sources (FREE):

  • literature/manifests/$(printf '%04d' $ARGUMENTS).yaml - Reference metadata (IDs are zero-padded, e.g. 6 → 0006.yaml)
  • literature/cache/ - Downloaded papers and sources
  • research/problems/$(printf '%04d' $ARGUMENTS)/ - Research workspace (leads, hypotheses, tasks)
  • Search index: uv run erdos search "relevant terms" --problem $ARGUMENTS (omit --problem to search globally)

Optional API sources (rate-limited, mostly free):

  • uv run erdos refs zbmath --msc <relevant-code> - zbMATH (free)
  • uv run erdos refs s2 citations <doi> - Semantic Scholar (rate-limited)
  • uv run erdos ingest $ARGUMENTS --source openalex - Fetch refs by DOI/arXiv ID (free)

Optional AI-powered discovery (PAID):

  • uv run erdos research exa search $ARGUMENTS "relevant query" --save-leads - Exa AI search

Step 3: Generate Lean Skeleton

Create the formal statement file:

bash
1uv run erdos lean formalize $ARGUMENTS

This creates: formal/lean/Erdos/Problem$(printf '%03d' $ARGUMENTS).lean (IDs are zero-padded, e.g. 6 → Problem006.lean)

What this generates:

  • Import statements for Mathlib
  • Formal theorem statement (with sorry placeholder)
  • Comments with problem context

Step 4: Develop the Proof (SUBSCRIPTION)

Now we work together to fill in the proof. This is where your subscription pays off instead of API calls.

I will directly edit these files (no copy/paste needed):

  • formal/lean/Erdos/Problem$(printf '%03d' $ARGUMENTS).lean - The main proof file
  • data/problems_enriched.yaml - Update status when solved

My workflow:

  1. Read the generated Lean file
  2. Analyze the theorem statement
  3. Propose proof strategies
  4. Write Lean tactics step by step
  5. Edit the file directly - you just watch and run lean check

Proof development strategies:

  • Break into lemmas if complex
  • Use Mathlib tactics (simp, ring, norm_num, omega)
  • Apply relevant theorems from Mathlib
  • Build incrementally, checking each step

Step 5: Verify Compilation

Check that the proof compiles:

bash
1PROBLEM3=$(printf '%03d' $ARGUMENTS) 2uv run erdos lean check "formal/lean/Erdos/Problem${PROBLEM3}.lean"

Possible outcomes:

  • Success: Proof compiles, no sorry remaining
  • Errors: Type mismatches, tactic failures, missing imports
  • Warnings: Unused variables, style issues

Step 6: Iterate on Errors (SUBSCRIPTION)

When compilation fails, show me the error output and I'll:

  1. Diagnose the issue
  2. Propose fixes
  3. Edit the file directly
  4. Repeat until it compiles

Common fixes:

  • Import missing Mathlib modules
  • Adjust tactic arguments
  • Add intermediate steps
  • Fix type annotations

Workflow Commands Reference

bash
1# Generate skeleton (if not done) 2uv run erdos lean formalize $ARGUMENTS 3 4# Check compilation 5PROBLEM3=$(printf '%03d' $ARGUMENTS) 6uv run erdos lean check "formal/lean/Erdos/Problem${PROBLEM3}.lean" 7 8# View problem details 9uv run erdos show $ARGUMENTS 10 11# Search related literature 12uv run erdos search "relevant terms" --problem $ARGUMENTS # omit --problem to search globally 13 14# Check formalization status 15uv run erdos lean status $ARGUMENTS 16 17# View execution logs 18uv run erdos logs --problem-id $ARGUMENTS

What I Can Do For You

Read & Analyze:

  • Problem statements from YAML
  • Lean files (existing proofs, Mathlib source)
  • Literature (PDFs, markdown)
  • Error messages

Edit & Write:

  • Lean proof tactics
  • Helper lemmas
  • Type annotations
  • Import statements

Research:

  • Find relevant Mathlib theorems
  • Explore proof strategies
  • Identify useful tactics

Example Conversation

text
1You: /erdos-prove 6 2 3Claude: Let me start the proving workflow for Problem 6. 4 5[Step 1] Reading problem statement... 6Problem 6 is about... [explains math] 7 8[Step 2] Checking existing literature... 9Found 3 references in the manifest: [lists them] 10 11[Step 3] I see formal/lean/Erdos/Problem006.lean exists. Let me read it... 12Current state: Has `sorry` at line 42. 13 14[Step 4] Here's my proposed proof approach: 151. We can use the pigeonhole principle 162. Apply Mathlib's Finset.card_le_card 173. Conclude with norm_num 18 19Let me edit the file to add the proof... 20[Makes edit] 21 22[Step 5] Now run: uv run erdos lean check formal/lean/Erdos/Problem006.lean 23 24You: [pastes error output] 25 26Claude: I see the issue - we need to import Data.Nat.Prime. 27Let me fix that... 28[Makes edit] 29 30Try again: uv run erdos lean check formal/lean/Erdos/Problem006.lean

Why This Saves Money

Traditional ApproachSubscription Approach
erdos loop run 6Work with Claude Code
~$0.50-5.00 per run$0 (subscription)
Automated but costlyInteractive but free
Limited iterationsUnlimited iterations

Alternative: Aristotle API (Paid)

If you prefer hands-off automated proving via Harmonic's Aristotle API:

bash
1# 1. Install aristotlelib 2uv sync --extra aristotle 3 4# 2. Set API key (use export for direct CLI calls) 5export ARISTOTLE_API_KEY=arstl-your-key 6 7# 3. Run via erdos wrapper (recommended - auto-loads .env) 8uv run erdos lean prove formal/lean/Erdos/Problem006.lean \ 9 --output formal/lean/Erdos/Problem006_aristotle.lean 10 11# Or direct CLI (requires exported env var) 12uv run aristotle prove-from-file \ 13 formal/lean/Erdos/Problem006.lean \ 14 --output-file formal/lean/Erdos/Problem006_aristotle.lean

Cost: Paid per-problem. Use the subscription workflow above for unlimited iterations.

Ready to Begin?

Tell me to start and I'll begin Step 1: reading and understanding Problem $ARGUMENTS.

Or if you want to jump to a specific step:

  • "Skip to step 3, the skeleton already exists"
  • "Start from step 4, I have the Lean file ready"
  • "I have errors, help me with step 6"

관련 스킬

Looking for an alternative to erdos-prove or another community skill for your workflow? Explore these related open-source skills.

모두 보기

openclaw-release-maintainer

Logo of openclaw
openclaw

현지화된 요약: 🦞 # OpenClaw Release Maintainer Use this skill for release and publish-time workflow. It covers ai, assistant, crustacean workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

333.8k
0
인공지능

nextjs-turbopack

[ 추천 ]
Logo of affaan-m
affaan-m

현지화된 요약: Next.js 16+ and Turbopack — incremental bundling, FS caching, dev speed, and when to use Turbopack vs webpack. It covers ai-agents, anthropic, claude workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

169.5k
0
생산성

widget-generator

Logo of f
f

현지화된 요약: Generate customizable widget plugins for the prompts.chat feed system # Widget Generator Skill This skill guides creation of widget plugins for prompts.chat . It covers ai, artificial-intelligence, awesome-list workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf

149.6k
0
인공지능

flags

Logo of vercel
vercel

현지화된 요약: The React Framework # Feature Flags Use this skill when adding or changing framework feature flags in Next.js internals. It covers blog, browser, compiler workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

138.4k
0
브라우저