Fix: Ensure all skills are tracked as files, not submodules
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# Loki Mode Benchmark Results
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**Generated:** 2026-01-05 01:10:21
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## Overview
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This directory contains benchmark results for Loki Mode multi-agent system.
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## HumanEval Results
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| Metric | Value |
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|--------|-------|
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| Problems | 164 |
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| Passed | 161 |
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| Failed | 3 |
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| **Pass Rate** | **98.17%** |
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| Model | opus |
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| Time | 1263.46s |
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### Competitor Comparison
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| System | Pass@1 |
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|--------|--------|
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| MetaGPT | 85.9-87.7% |
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| **Loki Mode** | **98.17%** |
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## Methodology
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Loki Mode uses its multi-agent architecture to solve each problem:
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1. **Architect Agent** analyzes the problem
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2. **Engineer Agent** implements the solution
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3. **QA Agent** validates with test cases
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4. **Review Agent** checks code quality
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This mirrors real-world software development more accurately than single-agent approaches.
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## Running Benchmarks
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```bash
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# Setup only (download datasets)
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./benchmarks/run-benchmarks.sh all
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# Execute with Claude
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./benchmarks/run-benchmarks.sh humaneval --execute
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./benchmarks/run-benchmarks.sh humaneval --execute --limit 10 # First 10 only
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./benchmarks/run-benchmarks.sh swebench --execute --limit 5 # First 5 only
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# Use different model
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./benchmarks/run-benchmarks.sh humaneval --execute --model opus
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```
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