prove▌
parcadei/continuous-claude-v3 · updated Apr 8, 2026
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For mathematicians who want verified proofs without learning Lean syntax.
/prove - Machine-Verified Proofs (5-Phase Workflow)
For mathematicians who want verified proofs without learning Lean syntax.
Prerequisites
Before using this skill, check Lean4 is installed:
# Check if lake is available
command -v lake &>/dev/null && echo "Lean4 installed" || echo "Lean4 NOT installed"
If not installed:
# Install elan (Lean version manager)
curl https://raw.githubusercontent.com/leanprover/elan/master/elan-init.sh -sSf | sh
# Restart shell, then verify
lake --version
First run of /prove will download Mathlib (~2GB) via lake build.
Usage
/prove every group homomorphism preserves identity
/prove Monsky's theorem
/prove continuous functions on compact sets are uniformly continuous
The 5-Phase Workflow
┌─────────────────────────────────────────────────────────────┐
│ 📚 RESEARCH → 🏗️ DESIGN → 🧪 TEST → ⚙️ IMPLEMENT → ✅ VERIFY │
└─────────────────────────────────────────────────────────────┘
Phase 1: RESEARCH (before any Lean)
Goal: Understand if/how this can be formalized.
-
Search Mathlib with Loogle (PRIMARY - type-aware search)
# Use loogle for type signature search - finds lemmas by shape loogle-search "pattern_here" # Examples: loogle-search "Nontrivial _ ↔ _" # Find Nontrivial lemmas loogle-search "(?a → ?b) → List ?a → List ?b" # Map-like functions loogle-search "IsCyclic, center" # Multiple conceptsQuery syntax:
_= any single type?a,?b= type variables (same var = same type)Foo, Bar= must mention both
-
Search External - What's the known proof strategy?
- Use Nia MCP if available:
mcp__nia__search - Use Perplexity MCP if available:
mcp__perplexity__search - Fall back to WebSearch for papers/references
- Check: Is there an existing formalization elsewhere (Coq, Isabelle)?
- Use Nia MCP if available:
-
Identify Obstacles
- What lemmas are NOT in Mathlib?
- Does proof require axioms beyond ZFC? (Choice, LEM, etc.)
- Is the statement even true? (search for counterexamples)
-
Output: Brief summary of proof strategy and obstacles
CHECKPOINT: If obstacles found, use AskUserQuestion:
- "This requires [X]. Options: (a) restricted version, (b) accept axiom, (c) abort"
Phase 2: DESIGN (skeleton with sorries)
Goal: Build proof structure before filling details.
-
Create Lean file with:
- Imports
- Definitions needed
- Main theorem statement
- Helper lemmas as
sorry
-
Annotate each sorry:
-- SORRY: needs proof (straightforward) -- SORRY: needs proof (complex - ~50 lines) -- AXIOM CANDIDATE: v₂ constraint - will test in Phase 3 -
Verify skeleton compiles (with sorries)
Output: proofs/<theorem_name>.lean with annotated structure
Phase 3: TEST (counterexample search)
Goal: Catch false lemmas BEFORE trying to prove them.
For each AXIOM CANDIDATE sorry:
-
Generate test cases
-- Create #eval or example statements #eval testLemma (randomInput1) -- should return true #eval testLemma (randomInput2) -- should return true -
Run tests
lake env lean test_lemmas.lean -
If counterexample found:
- Report the counterexample
- Use AskUserQuestion: "Lemma is FALSE. Options: (a) restrict domain, (b) reformulate, (c) abort"
CHECKPOINT: Only proceed if all axiom candidates pass testing.
Phase 4: IMPLEMENT (fill sorries)
Goal: Complete the proofs.
Standard iteration loop:
- Pick a sorry
- Write proof attempt
- Compiler-in-the-loop checks (hook fires automatically)
- If error, Godel-Prover suggests fixes
- Iterate until sorry is filled
- Repeat for all sorries
Tools active:
- compiler-in-the-loop hook (on every Write)
- Godel-Prover suggestions (on errors)
Phase 5: VERIFY (audit)
Goal: Confirm proof quality.
-
Axiom Audit
lake build && grep "depends on axioms" output- Standard: propext, Classical.choice, Quot.sound ✓
- Custom axioms: LIST EACH ONE
-
Sorry Count
grep -c "sorry" proofs/<file>.lean- Must be 0 for "complete" proof
-
Generate Summary
✓ MACHINE VERIFIED (or ⚠️ PARTIAL - N axioms) Theorem: <statement> Proof Strategy: <brief description> Proved: - <lemma 1> - <lemma 2> Axiomatized (if any): - <axiom>: <why it's needed> File: proofs/<name>.lean
Research Tool Priority
Use whatever's available, in order:
| Tool | Best For | Command |
|---|---|---|
| Loogle | Type signature search (PRIMARY) | loogle-search "pattern" |
| Nia MCP | Library documentation | mcp__nia__search |
| Perplexity MCP | Proof strategies, papers | mcp__perplexity__search |
| WebSearch | General references | WebSearch tool |
| WebFetch | Specific paper/page content | WebFetch tool |
Loogle setup: Requires ~/tools/loogle with Mathlib index. Run loogle-server & for fast queries.
If no search tools available, proceed with caution and note "research phase skipped".
Checkpoints (automatic)
The workflow pauses for user input when:
- ⚠️ Research finds obstacles
- ❌ Testing finds counterexamples
- 🔄 Implementation hits unfillable sorry after N attempts
Output Format
┌─────────────────────────────────────────────────────┐
│ ✓ MACHINE VERIFIED │
│ │
│ Theorem: ∀ φ : G →* H, φ(1_G) = 1_H │
│ │
│ Proof Strategy: Direct application of │
│ MonoidHom.map_one from Mathlib. │
│ │
│ Phases: │
│ 📚 Research: Found in Mathlib.Algebra.Group.Hom │
│ 🏗️ Design: Single lemma, no sorries needed │
│ 🧪 Test: N/A (trivial) │
│ ⚙️ Implement: 3 lines │
│ ✅ Verify: 0 custom axioms, 0 sorries │
│ │
│ File: proofs/group_hom_identity.lean │
└─────────────────────────────────────────────────────┘
What I Can Prove
| Domain | Examples |
|---|---|
| Category Theory | Functors, natural transformations, Yoneda |
| Abstract Algebra | Groups, rings, homomorphisms |
| Topology | Continuity, compactness, connectedness |
| Analysis | Limits, derivatives, integrals |
| Logic | Propositional, first-order |
Limitations
- Complex proofs may take multiple iterations
- Novel research-level proofs may exceed capabilities
- Some statements are unprovable over ℚ (need ℝ extension)
Behind The Scenes
- Lean 4.26.0 - Theorem prover
- Mathlib - 100K+ formalized theorems
- Godel-Prover - AI tactic suggestions (via LMStudio)
- Compiler-in-the-loop - Automatic verification on every write
- Research tools - Nia, Perplexity, WebSearch (graceful degradation)
See Also
/loogle-search- Search Mathlib by type signature (used in Phase 1 RESEARCH)/math-router- For computation (integrals, equations)/lean4- Direct Lean syntax access
How to use prove on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add prove
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches prove from GitHub repository parcadei/continuous-claude-v3 and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate prove. Access the skill through slash commands (e.g., /prove) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★29 reviews- ★★★★★Alexander Diallo· Dec 24, 2024
prove has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Shikha Mishra· Dec 8, 2024
prove reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Zara Johnson· Dec 8, 2024
Useful defaults in prove — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Zara Sharma· Dec 4, 2024
Registry listing for prove matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Ira Verma· Nov 27, 2024
prove is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Diya Diallo· Nov 15, 2024
prove fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Soo Desai· Oct 18, 2024
Keeps context tight: prove is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Diya Rahman· Oct 6, 2024
We added prove from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ira Tandon· Sep 25, 2024
Useful defaults in prove — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Oshnikdeep· Sep 13, 2024
prove has been reliable in day-to-day use. Documentation quality is above average for community skills.
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