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**Main Goal**: Port numpy functionality to Lean 4 with AI, using bootstrapping from feedback like compiler error messages. Formal verification is used as a way to gain signal for bootstrapping.
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## IMPORTANT: "Keep Going" Context
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If you're told to "keep going" without context, you're likely working on:
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1.**DafnyBenchmarks Porting** - See [NumpySpec/DafnyBenchmarks/CLAUDE.md](NumpySpec/DafnyBenchmarks/CLAUDE.md)
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- Port Batch 6: Tasks 616, 470, 578, 240, 572, etc. (20 numeric-only tasks)
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- Follow the complete workflow documented there
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2.**NumPy Function Implementation** - Continue implementing NumPy functions with specs
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3.**Test Writing** - Add more property-based tests using Plausible
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## General Programming Philosophy
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Programming is about onomastics (naming), composition (functoriality), and caching. Think conformally at every scale and across scales.
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## Project Structure
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-`NumpySpec.lean` and `NumpySpec/` directory - core numpy functionality.
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-`NumpySpec/DafnyBenchmarks/` - Porting Dafny specifications to Lean 4 (see [DafnyBenchmarks/CLAUDE.md](NumpySpec/DafnyBenchmarks/CLAUDE.md))
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-**Current Status**: 90 specifications ported across 5 batches
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-**Next**: Continue with Batch 6 (20 numeric-only tasks)
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-`FuncTracker.lean` and `FuncTracker/` directory - ASCII table parsing for presenting development progress to boss.
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-`lakefile.lean` - Lean 4 project configuration.
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## Development Tools and Workflow
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### Task Delegation
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- Use `codex` for delegating tasks to sub-agents: `codex -q --project-doc CLAUDE.md -a full-auto "<task>"`
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- Sub-agents can recursively invoke other sub-agents
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- Use `terminal-notifier` to get completion notifications
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### Version Control
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**Jujutsu (jj) Setup for GitHub-friendly Development:**
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