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Hle Benchmark Evolver
Runs HLE-oriented benchmark reward ingestion and curriculum generation for capability-evolver. Use when the user asks to optimize Humanity's Last Exam score,...
安全通过
⚙️脚本
技能说明
name: hle-benchmark-evolver description: Runs HLE-oriented benchmark reward ingestion and curriculum generation for capability-evolver. Use when the user asks to optimize Humanity's Last Exam score, ingest question-level benchmark results, prioritize easy-first queues, or request an immediate benchmark progress result. tags: [benchmark, hle, evolution, reward, curriculum]
HLE Benchmark Evolver
This skill operationalizes HLE score-driven evolution for OpenClaw.
When to Use
- User asks to improve HLE score (for example target >= 60%).
- User provides question-level benchmark output and wants it converted to reward.
- User wants easy-first curriculum queue and next-focus questions.
- User asks for an immediate benchmark result snapshot.
Inputs
- Benchmark report JSON path (
--report=/abs/path/report.json) - Optional benchmark id (
cais/hledefault)
Workflow
- Validate the report JSON exists and is parseable.
- Ingest report into
capability-evolverbenchmark reward state. - Generate curriculum signals:
benchmark_*curriculum_stage:*focus_subject:*focus_modality:*question_focus:*
- Return a compact result summary for this run.
Run
node skills/hle-benchmark-evolver/run_result.js --report=/absolute/path/hle_report.json
Full automatic loop (starts evolution cycle):
node skills/hle-benchmark-evolver/run_pipeline.js --report=/absolute/path/hle_report.json --cycles=1
If your evaluator can be called from shell, let pipeline generate the report each cycle:
node skills/hle-benchmark-evolver/run_pipeline.js \
--report=/absolute/path/hle_report.json \
--eval_cmd="python /path/to/eval_hle.py --out {{report}}" \
--cycles=3 --interval_ms=2000
If no --report is provided, it defaults to:
skills/capability-evolver/assets/gep/hle_report.template.json
Output Contract
Always print JSON with these fields:
benchmark_idrun_idaccuracyrewardtrendcurriculum_stagequeue_sizefocus_subjectsfocus_modalitiesnext_questions
Notes
- This skill handles reward/curriculum ingestion. It does not directly solve HLE questions.
run_pipeline.jslinks ingestion, evolve, and solidify into one executable loop.
如何使用「Hle Benchmark Evolver」?
- 打开小龙虾AI(Web 或 iOS App)
- 点击上方「立即使用」按钮,或在对话框中输入任务描述
- 小龙虾AI 会自动匹配并调用「Hle Benchmark Evolver」技能完成任务
- 结果即时呈现,支持继续对话优化