77 lines
1.9 KiB
YAML
77 lines
1.9 KiB
YAML
# SWE-bench Submission Metadata
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# For Loki Mode Multi-Agent System
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# Model Information
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model:
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name: "loki-mode"
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version: "2.25.0"
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base_model: "claude-opus-4-5-20251101"
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type: "multi-agent-system"
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# System Architecture
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architecture:
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type: "multi-agent-pipeline"
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agents:
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- name: "Architect"
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role: "Analyze issue and design fix approach"
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model: "claude-opus-4.5"
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timeout: 120
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- name: "Engineer"
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role: "Generate patch based on architect's analysis"
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model: "claude-opus-4.5"
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timeout: 300
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- name: "QA"
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role: "Validate patch format"
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model: "rule-based"
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timeout: 5
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- name: "Reviewer"
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role: "Analyze issues and suggest fixes"
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model: "claude-opus-4.5"
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timeout: 60
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# RARV Cycle (Reason-Act-Reflect-Verify)
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rarv:
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enabled: true
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max_retries: 3
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description: "Self-verification loop that retries failed patches with reviewer feedback"
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# Benchmark Configuration
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benchmark:
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dataset: "SWE-bench_Lite"
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split: "test"
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total_problems: 300
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# Results Summary
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results:
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patch_generation_rate: 99.67
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problems_solved: 299
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problems_total: 300
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fixed_by_rarv: 0
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avg_attempts: 1.0
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total_time_seconds: 12600
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avg_time_per_problem_seconds: 42
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# Submission Information
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submission:
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date: "2026-01-05"
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author: "Loki Mode Team"
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repository: "https://github.com/asklokesh/loki-mode"
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license: "MIT"
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# Contact
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contact:
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email: "lokesh@example.com"
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github: "asklokesh"
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# Notes
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notes: |
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Loki Mode is a multi-agent system built as a Claude Code skill.
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It uses a 4-agent pipeline (Architect -> Engineer -> QA -> Reviewer)
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with a RARV (Reason-Act-Reflect-Verify) cycle for self-correction.
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Key features:
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- Multi-agent coordination for complex problem solving
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- Automatic retry with reviewer feedback on failures
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- Full trajectory logging for transparency
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- Matches single-agent performance after timeout optimization
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