What problem does it solve? Running connections-checker end-to-end evaluations involves dispatching GitHub workflows, polling the genai-eval AllSpice Hub for results, and judging noisy metrics against baselines. This Skill encodes that entire procedure so a single E2E round is executed and interpreted correctly without relearning the pitfalls each time. ## Core Features & Use Cases - Dispatch and follow runs: Kick off e2e_manual.yml with a full 40-character SHA, then poll run status, design reviews, and comments via the hub.py helper script. - Summarize results: Use summarize.py to condense rubric judge comments and metrics-index bands into compact per-run blocks for comparison against main baselines. - Pull artifacts and traces: Download eval_output artifacts with pull_artifact.py to inspect rendered page input, model reasoning groups, and verifier confidence reports. - Use Case: After pushing a branch that changes how KiCad schematics are rendered, dispatch an E2E round, wait 15-25 minutes, then compare caught rubric items and token usage against four recent main baselines to confirm the change engaged without regressions. ## Quick Start Ask the assistant to run an E2E round for the current connections-checker branch and report how it compares to recent main baselines.