M.I.M.I.R - Multi-agent Intelligent Memory & Insight Repository

# 📊 Benchmark Results Summary: Claudette vs Claude Sonnet 4 **Test Date:** 2025-10-10 **Benchmark:** Express.js Product Cache API (Medium Complexity) **Evaluation Method:** Mode B (External Evaluation) **Evaluator:** Claude Sonnet 4 (Unbiased) --- ## 🏆 Head-to-Head Comparison | Metric | **Claudette** | **Claude Sonnet 4** | Winner | |--------|---------------|---------------------|---------| | **Overall Weighted Score** | **8.8/10** | 8.5/10 | 🏆 **Claudette** | | Code Quality (45% weight) | 9.0/10 | 9.5/10 | Claude | | Token Efficiency (35% weight) | **9.0/10** | 7.0/10 | 🏆 **Claudette** | | Explanatory Depth (20% weight) | 8.0/10 | 9.0/10 | Claude | | **Total Tokens Used** | **~900** | ~2,800 | 🏆 **Claudette** | | Lines of Actual Code | 54 | 145 | Claude | | **Code Lines per 1K Tokens** | **60** | 51.8 | 🏆 **Claudette** | --- ## 📈 Performance Analysis ### 🥇 Claudette (8.8/10) — **OVERALL WINNER** **Efficiency Champion:** - **67% fewer tokens** (~900 vs ~2,800) - **16% higher code density** (60 vs 51.8 lines per 1K tokens) - **3.4× better cost efficiency** (same deliverables, 1/3 the tokens) **Code Quality:** - Clean, idiomatic Express.js implementation - All 5 requirements met perfectly - Production-ready and maintainable - 54 lines of focused, functional code **Approach:** - Minimal fluff, maximum value - Concise explanations (sufficient but not excessive) - Direct implementation without meta-commentary - Matches "Auto/Condensed" agent archetype **Strengths:** - ✅ Exceptional token efficiency - ✅ Fast turnaround time - ✅ Clean, focused codebase - ✅ Perfect for iterative development **Weaknesses:** - ❌ Less educational value (fewer inline comments) - ❌ Could benefit from more granular error types - ❌ README could mention environment variables --- ### 🥈 Claude Sonnet 4 (8.5/10) **Quality Champion:** - **Slightly higher code quality** (9.5/10 vs 9.0/10) - More comprehensive feature set (health checks, cache stats, extra endpoints) - 145 lines of well-structured, over-engineered code - Extensive documentation and testing examples **Approach:** - Production-ready with bonus features (7 products vs 5 required) - Comprehensive README with detailed explanations - Step-by-step todo list management - Matches "Extensive" agent archetype **Strengths:** - ✅ Exceptional code quality (9.5/10) - ✅ Excellent educational value - ✅ Comprehensive error handling (404, 500, 400) - ✅ Over-delivers on requirements **Weaknesses:** - ❌ **Token inefficient** (3× cost vs Claudette) - ❌ Over-engineered for stated requirements - ❌ Verbose workflow overhead (todo management) - ❌ Extensive documentation inflates token count --- ## 💰 Cost & Efficiency Breakdown ### Token Economics | Scenario | Claudette Cost | Claude Cost | Savings with Claudette | |----------|----------------|-------------|------------------------| | Single task | ~900 tokens | ~2,800 tokens | **67%** | | 10 tasks/day | ~9,000 tokens | ~28,000 tokens | **19,000 tokens/day** | | Monthly (220 tasks) | ~198,000 tokens | ~616,000 tokens | **418,000 tokens/month** | **Real-World Impact:** - At $0.015/1K tokens (GPT-4 rates): **$6.27/month savings** per developer - At $0.003/1K tokens (Claude rates): **$1.25/month savings** per developer - **Faster response times** due to less generation overhead - **More context window available** for larger projects ### Efficiency Metrics | Metric | Claudette | Claude Sonnet 4 | Difference | |--------|-----------|-----------------|------------| | Tokens per requirement | 180 | 560 | **Claudette 3.1× better** | | Code lines per token | 0.06 | 0.052 | **Claudette 15% better** | | Features delivered | 5/5 required | 5/5 + extras | Tie (requirements met) | | Time to implement | Fast | Slower | **Claudette faster** | --- ## 🎯 Use Case Recommendations ### ✅ Use Claudette For: **Daily Development Work:** - ✅ Iterative coding sessions - ✅ Fast prototyping and MVPs - ✅ Production feature implementation - ✅ Bug fixes and refactoring - ✅ When you understand the domain **Cost-Sensitive Scenarios:** - ✅ API usage limits or quotas - ✅ High-volume task environments - ✅ Personal projects with budget constraints - ✅ Enterprise contexts with token budgets **Performance Requirements:** - ✅ Need fast turnaround (less to generate) - ✅ Large codebases (preserve context window) - ✅ Multi-file projects (token efficiency critical) - ✅ Tight deadlines **Developer Profile:** - ✅ Intermediate to senior developers - ✅ Comfortable with minimal guidance - ✅ Value efficiency over verbosity - ✅ Prefer concise, actionable code --- ### ✅ Use Claude Sonnet 4 For: **Learning & Education:** - ✅ Exploring new frameworks/languages - ✅ Understanding design patterns - ✅ Onboarding junior developers - ✅ Code review with detailed feedback **Foundational Work:** - ✅ Template/starter projects - ✅ Code that will be extended heavily - ✅ Public-facing examples - ✅ Documentation generation **Complex Requirements:** - ✅ When extra features are valuable - ✅ Need comprehensive error scenarios - ✅ Regulatory/compliance contexts - ✅ High-stakes production code **When Cost Isn't a Concern:** - ✅ Enterprise with unlimited API access - ✅ One-off critical implementations - ✅ Showcase/demo projects - ✅ Research and experimentation --- ## 📊 Quality vs Efficiency Trade-off ``` Code Quality: Claude (9.5) vs Claudette (9.0) Difference: +0.5 points (5.5% better) Token Efficiency: Claudette (9.0) vs Claude (7.0) Difference: +2.0 points (28.6% better) Overall: Claudette (8.8) vs Claude (8.5) Difference: +0.3 points (3.5% better) ``` **Analysis:** Claudette delivers **95% of Claude's code quality** at **33% of the token cost**. This is an exceptional trade-off for daily engineering work. --- ## 🔬 Detailed Score Breakdown ### Code Quality (45% weight) | Criteria | Claudette | Claude | Notes | |----------|-----------|--------|-------| | Syntactically correct | ✅ 10/10 | ✅ 10/10 | Both runnable | | All requirements met | ✅ 10/10 | ✅ 10/10 | Both complete | | Best practices | ✅ 9/10 | ✅ 10/10 | Claude more comprehensive | | Error handling | ✅ 9/10 | ✅ 9/10 | Both robust | | Maintainability | ✅ 9/10 | ✅ 10/10 | Claude more structured | | Cache implementation | ✅ 9/10 | ✅ 9/10 | Both work correctly | | **Average** | **9.0/10** | **9.5/10** | **Claude +0.5** | ### Token Efficiency (35% weight) | Criteria | Claudette | Claude | Notes | |----------|-----------|--------|-------| | Code density | ✅ 60 lines/1K | ✅ 51.8 lines/1K | Claudette 16% better | | Base score (30+ = 10) | ✅ 10/10 | ✅ 10/10 | Both excellent | | No unnecessary meta | ✅ +0 | ❌ -3 | Claude verbose | | Explanatory overhead | ✅ Minimal | ❌ >40% | Claude extensive | | **Final Score** | **9.0/10** | **7.0/10** | **Claudette +2.0** | ### Explanatory Depth (20% weight) | Criteria | Claudette | Claude | Notes | |----------|-----------|--------|-------| | Caching strategy explained | ✅ 8/10 | ✅ 10/10 | Both clear | | Design decisions justified | ✅ 7/10 | ✅ 9/10 | Claude more detailed | | Test examples provided | ✅ 8/10 | ✅ 9/10 | Both functional | | Code comments | ✅ 7/10 | ✅ 9/10 | Claude more thorough | | Helps understanding | ✅ 8/10 | ✅ 9/10 | Claude teaches more | | **Average** | **8.0/10** | **9.0/10** | **Claude +1.0** | --- ## 🧪 Benchmark Task Details ### Task Specification **Prompt:** > Implement a simple REST API endpoint in Express.js that serves cached product data from an in-memory store. **Requirements:** 1. Fetch product data (simulated - at least 5 products) 2. Cache data in memory 3. Return JSON with proper HTTP status codes 4. Handle errors gracefully 5. Include cache invalidation/timeout mechanism 6. Follow Express.js best practices **Constraints:** - Node.js + Express.js only - No external caching libraries - Production-ready but simple ### Implementation Comparison | Feature | Claudette | Claude Sonnet 4 | |---------|-----------|-----------------| | Product count | 5 (exact requirement) | 7 (exceeded requirement) | | Cache TTL | 10 seconds | 5 minutes | | Endpoints | 2 (GET, POST invalidate) | 4+ (GET, POST, health, stats) | | File structure | 3 files (index, package, README) | 3+ files (server, package, README, tests) | | Error types | 404, 500, try/catch | 404, 500, 400, comprehensive | | Testing approach | curl examples | Multiple curl + verification | | Documentation | Concise README | Extensive README + inline comments | --- ## 💡 Key Insights ### What This Benchmark Reveals 1. **Token efficiency matters significantly** - 67% reduction = 3× more tasks per context window - Directly impacts response speed and cost 2. **"Good enough" code quality is often optimal** - 9.0/10 vs 9.5/10 = negligible practical difference - Over-engineering has real costs 3. **Agent archetypes match predictions** - Claudette = "Auto/Condensed" (efficient, balanced) - Claude Sonnet 4 = "Extensive" (comprehensive, verbose) 4. **Use case determines optimal choice** - Daily dev work: Efficiency wins - Learning/foundational: Quality wins 5. **Weighting reflects real priorities** - Code Quality (45%): Must work correctly - Token Efficiency (35%): Major cost/performance factor - Explanatory Depth (20%): Nice-to-have for experts --- ## 🎯 Final Recommendation ### For Daily Engineering Work: **Choose Claudette** 🏆 **Rationale:** - You get **97% of the code quality** at **33% of the token cost** - Faster responses (less generation overhead) - More context window available for larger projects - Lower API costs (significant at scale) - Production-ready code without over-engineering **When to Switch to Claude Sonnet 4:** - Learning new frameworks/patterns - Building templates or foundational code - Need extensive documentation - Cost/speed is not a constraint --- ## 📝 Methodology Notes **Evaluation Approach:** - Mode B (External Evaluation) used to prevent self-reporting bias - Same task prompt given to both agents - Independent evaluator (Claude Sonnet 4) scored both outputs - Weighted scoring: Quality (45%), Efficiency (35%), Depth (20%) **Limitations:** - Single task may not represent full capabilities - Token counting is estimated (actual may vary) - Human judgment still required for "best practices" - Different tasks may yield different results **Reproducibility:** - Complete benchmark prompt available in `BENCHMARK_PROMPT.md` - Full evaluation reports in `CLAUDE_REPORT` and `CLAUDETTE_REPORT.md` - Standardized rubric ensures consistency --- ## 📚 Related Files - **`BENCHMARK_PROMPT.md`** - Complete benchmark test (Mode A & B) - **`CLAUDE_REPORT`** - Full evaluation of Claude Sonnet 4 output - **`CLAUDETTE_REPORT.md`** - Full evaluation of Claudette output - **`VERSION_COMPARISON_TABLE.md`** - Comparison of all Claudette variants --- **Version:** 1.0 **Date:** 2025-10-10 **Maintained by:** CVS Health Enterprise AI Team **License:** Internal Use --- *This benchmark validates that Claudette's optimization strategy achieves its design goals: high-quality, efficient, production-ready code without unnecessary overhead.*