{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "metaevo-ai-harness-zero--reproduce-appworld-evaluation",
 "repo": "metaevo-ai/harness-zero",
 "repo_url": "https://github.com/metaevo-ai/harness-zero",
 "repo_slug": "metaevo-ai-harness-zero",
 "title": "Reproduce the AppWorld evaluation with the dedicated setup",
 "page_title": "How to reproduce the AppWorld evaluation with the dedicated setup with Harness Zero",
 "summary": "Run AppWorld rollouts through the included mini-SWE-agent and environment to match the reported setup.",
 "who": "A benchmark researcher who needs to check AppWorld results against the paper's test_normal split.",
 "problem": "AppWorld rollouts fail or give misleading scores when run with a generic harness instead of the dedicated agent and environment.",
 "outcome": "AppWorld rollouts that use the dedicated envs/appworld agent and environment, with SGC scores on the 168 test tasks.",
 "steps": [
  "Run `uv sync` in the repo folder.",
  "Read envs/appworld/README.md, which the README says AppWorld rollouts must follow.",
  "Build the AppWorld image and environment as described in envs/appworld/README.md.",
  "Run the AppWorld rollouts with the dedicated mini-SWE-agent and environment, then compare SGC against the test_normal numbers in the README."
 ],
 "agent_prompt": "Using the repo metaevo-ai/harness-zero, follow envs/appworld/README.md to run AppWorld test_normal rollouts with the dedicated agent and environment. Expected output: SGC scores across the 168 test tasks. Verify that the run uses the dedicated environment and not a generic harness before reporting scores.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "4 hours",
 "basis": "readme",
 "caveat": "The README says AppWorld rollouts must use the dedicated environment, so results from other setups are not comparable to the paper.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.12 to 3.13 and uv installed",
  "Docker running, since rollouts run in local Docker sandboxes via Harbor",
  "API key for your model route (OpenAI, Azure AI Foundry, or OpenRouter) in a .env file copied from .env.example",
  "A Tinker key (TM_API_KEY) if you plan to run training"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/metaevo-ai-harness-zero/reproduce-appworld-evaluation/",
 "md": "https://dedupedai.com/use-cases/metaevo-ai-harness-zero/reproduce-appworld-evaluation/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/metaevo-ai-harness-zero--reproduce-appworld-evaluation.json",
 "api_version": "v1"
}