Show HN: An AI agent skill repo built around evals, not demos
## Sebastian's Benchmarked Skills Reusable AI age…
Sebastian's Benchmarked Skills
Reusable AI agent skills, each with a regression eval track record. That track record is the main artifact, so start there before cloning or running anything.
Review the evals
The 2026 World Cup has wrapped, but the eval track record lives on and is still worth a look.
Dashboard Best for
Trend dashboard → Top-line metrics and regression trends over time
Harbor dashboard → The complete historical record of every job and task trial
Or browse the same history locally after cloning:
runme eval view
Use a skill
Install world-cup-picks-report globally from this repo:
npx skills add -g https://github.com/sourishkrout/skills --skill world-cup-picks-report
Or add it through the Claude Code marketplace:
/plugin marketplace add sourishkrout/skills /plugin install world-cup-picks-report@sourishkrout-skills
Contributing
Everything below is for running, promoting, and deploying the evals locally.
Runme's eval workflow is documented at https://docs.runme.dev/eval/ .
Current skill:
- world-cup-picks-report in skills/world-cup-picks-report
Run the evals
The regression verifier uses Anthropic-backed LLM judges. Export an Anthropic API key before running the evals:
export ANTHROPIC_API_KEY=...
Run the full regression eval from the repo root:
runme eval skills/world-cup-picks-report/evals/regression
--agent codex
--ak reasoning_effort=xhigh
To run only the oracle:
runme eval skills/world-cup-picks-report/evals/regression
You can substitute another supported agent, such as cursor-cli , claude-code , or openclaw , for codex .
Promote fresh results
After running an eval, compare the latest local job against the latest Git-tracked baseline:
runme eval compare skills/world-cup-picks-report/evals/regression
Preview the promotion before committing evidence:
runme eval promote skills/world-cup-picks-report/evals/regression --latest --dry-run
If the result should become the new baseline, stage the related source changes and promote the eval evidence:
git add < changed-files > runme eval promote skills/world-cup-picks-report/evals/regression --latest
Promotion records compact eval evidence by default. Use --artifacts only when you need full logs and trial outputs; artifacts can contain sensitive information. Use --evidence-only when promoting eval evidence without source changes.
Review artifacts before promoting, because the Harbor showcase is public. Push the promotion commit to main and GitHub Actions publishes the fresh results.
本条由桃子采集流水线(启发式模式)自动整理,原文见文末信源。
