jorcan/automejora_agentes/2026-01-05-01-35-39

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Install

npx vskill@latest install jorcan/automejora_agentes/2026-01-05-01-35-39

SKILL.md

Loki Mode Benchmark Results

Generated: 2026-01-05 02:32:40

Overview

This directory contains benchmark results for Loki Mode multi-agent system.

SWE-bench Lite Results

MetricValue
Problems50
Patches Generated50
Errors0
Modelopus
Time3413.75s

Next Step: Run the SWE-bench evaluator to validate patches:

bash
python -m swebench.harness.run_evaluation     --predictions /Users/lokesh/git/loki-mode/benchmarks/results/2026-01-05-01-35-39/swebench-predictions.json     --max_workers 4

Methodology

Loki Mode uses its multi-agent architecture to solve each problem:

  1. Architect Agent analyzes the problem
  2. Engineer Agent implements the solution
  3. QA Agent validates with test cases
  4. Review Agent checks code quality

This mirrors real-world software development more accurately than single-agent approaches.

Running Benchmarks

bash
# Setup only (download datasets)
./benchmarks/run-benchmarks.sh all
 
# Execute with Claude
./benchmarks/run-benchmarks.sh humaneval --execute
./benchmarks/run-benchmarks.sh humaneval --execute --limit 10  # First 10 only
./benchmarks/run-benchmarks.sh swebench --execute --limit 5    # First 5 only
 
# Use different model
./benchmarks/run-benchmarks.sh humaneval --execute --model opus

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

See the full security report

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

See evaluation results

Source

Popularity

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Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

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