{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "xiantingwu-verirepro--score-agent-reproduction-tasks-reprobench",
 "repo": "XiantingWu/VeriRepro",
 "repo_url": "https://github.com/XiantingWu/VeriRepro",
 "repo_slug": "xiantingwu-verirepro",
 "title": "Score agent reproduction runs with the ReproBench adapter",
 "page_title": "How to score agent reproduction runs with the ReproBench adapter with Veri Repro",
 "summary": "Turn each agent's reproduction task into a result file and a summary with the ReproBench commands.",
 "who": "An evaluator building or comparing AI agents on paper reproduction tasks who needs consistent, auditable results.",
 "problem": "Agents report reproduction outcomes in different formats, which makes them hard to compare and audit.",
 "outcome": "A per-task result JSON with outcome, comparisons, failure taxonomy, and provenance, plus one summary JSON across tasks.",
 "steps": [
  "Install the package with `python -m pip install verirepro`.",
  "Prepare a task JSON file for one reproduction task, using only the allowed paper sources and confined paths.",
  "Run the adapter on the task with `verirepro-reprobench task.json --output result.json`.",
  "Summarize all results with `verirepro-reprobench-summary results/*.json --output summary.json` and check that each result records its operator interventions."
 ],
 "agent_prompt": "Using the VeriRepro repo (XiantingWu/VeriRepro), run `verirepro-reprobench task.json --output result.json` for the task file <task-file>, then run `verirepro-reprobench-summary results/*.json --output summary.json`. Expected output is a per-task result and a combined summary. Verify that the task file had no local, file, or insecure HTTP paper sources and that operator interventions are recorded.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "1 hour",
 "basis": "readme",
 "caveat": "The adapter rejects local, file, and insecure HTTP paper sources, so tasks must use allowed paper sources to be accepted.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "python",
 "requirements": [
  "Python with pip to install the verirepro package from PyPI",
  "A pinned arXiv ID, DOI, PDF URL, or local PDF of the paper",
  "Docker, only if you want third-party experiment code to execute",
  "An OpenAI-compatible model endpoint, only if you want model-assisted analysis"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/xiantingwu-verirepro/score-agent-reproduction-tasks-reprobench/",
 "md": "https://dedupedai.com/use-cases/xiantingwu-verirepro/score-agent-reproduction-tasks-reprobench/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/xiantingwu-verirepro--score-agent-reproduction-tasks-reprobench.json",
 "api_version": "v1"
}