| What it does | Keep the why with your code
| Analyze time and space complexity, optimize code, and learn algorithms in one connected workflow
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| Stage | Not given
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| Pricing model | Open source
| Free
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| Pricing | Not given
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| Key features | - Records stated reasoning for changes the agent logs
- Entity-level attribution for code elements
- Retrieves recorded attempts and outcomes
- Groups related changes across files
- Full-text search over change history
- Exports to Agent Trace format
- Local SQLite storage with no hosted backend
- MCP and CLI interfaces
- Concurrent readers and writers with WAL mode
| - Real-time Big O complexity calculation for code snippets
- Support for multiple programming languages
- Best, worst, and average case complexity analysis
- Interactive learning paths for algorithms and data structures
- Pre-built examples for sorting, searching, graph, and other algorithms
- Comparison of original versus optimized code
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| What makes it different | - Zero network dependencies; all storage and history queries run locally
- Captures reasoning at the time of change from the agent's own context
- MIT-licensed open source with no vendor lock-in
- Works with any compatible AI agent through standard MCP protocol
- Validates reasoning quality to surface low-quality logs
| - Unified platform combining analysis, optimization, and learning in one workflow
- Human-friendly explanations prioritizing intuition over jargon
- No account required to access tools and learning material
- Structured learning progression from complexity basics to advanced algorithms
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 36 ● no change since last check | 2 ● no change since last check |
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| Trust Flow (Majestic) | 5 | 1 |
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| Citation Flow (Majestic) | 31 | 4 |
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| Referring domains (Majestic) | 97 | 2 |
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