{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "yinsongxu-llm2jev--score-drafts-against-a-rubric",
 "repo": "Yinsongxu/LLM2Jev",
 "repo_url": "https://github.com/Yinsongxu/LLM2Jev",
 "repo_slug": "yinsongxu-llm2jev",
 "title": "Score drafts against a rubric and yes/no checks",
 "page_title": "How to score drafts against a rubric and yes/no checks with LLM2 Jev",
 "summary": "Rate a text on rubric criteria and get yes/no probabilities for checks like policy compliance.",
 "who": "A content editor or a QA agent that reviews drafts against a fixed checklist before publishing.",
 "problem": "Reviewers apply rubrics inconsistently, and generated text needs a repeatable first pass.",
 "outcome": "Rubric scores from Score and yes/no probabilities from Noul, returned as typed Python objects or JSON in one request.",
 "steps": [
  "`git clone https://github.com/Yinsongxu/LLM2Jev.git`",
  "`cd LLM2Jev`",
  "`uv sync --extra sglang`",
  "`llm2jev-serve --backend sglang --model-path /path/to/model --served-model-name local-model --host 127.0.0.1 --port 30000` (inferred, check the README)",
  "Build one request that mixes a Score rubric and a Noul yes/no question, following the Usage guide section on the Python client (inferred, check the README)"
 ],
 "agent_prompt": "Using the LLM2Jev repo, call systemone.create on the running service with the draft text <draft-text>, a Score rubric for <rubric-criteria>, and a Noul yes/no check for <check-question>. Return the rubric scores and yes/no probabilities as JSON. Verify that each score is returned for every rubric item before reporting.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "1 hour 30 minutes",
 "basis": "readme",
 "caveat": "The README lists Score and Noul as question types but its quick start shows only Choice, so check the Usage guide for the exact Score and Noul arguments.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "A local model directory supported by SGLang, Transformers, or MLX (Apple Silicon)",
  "For the SGLang path: Linux with a supported NVIDIA GPU",
  "Python with uv or pip, as described in the Installation guide",
  "A text or image input to decide on"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.9,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/yinsongxu-llm2jev/score-drafts-against-a-rubric/",
 "md": "https://dedupedai.com/use-cases/yinsongxu-llm2jev/score-drafts-against-a-rubric/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/yinsongxu-llm2jev--score-drafts-against-a-rubric.json",
 "api_version": "v1"
}