{"data":{"kind":"file","path":"README.md","version_id":"ztkt4gxx5cydd3u6r65b7suy","entry":{"name":"README.md","path":"README.md","is_directory":false,"size":1266,"modified_at":"2026-02-02T17:43:23.762000","content_hash":"ceefdfd1d11456165be12853c5d4fb6474e30199c6152b7bb3ba42be0ba9a3e2"},"entries":[],"content":"# paperclips\n\n> Replace the placeholders below, then remove this callout.\n\n### Overview\n- **Environment ID**: `paperclips`\n- **Short description**: an llm agent to play the game: https://www.decisionproblem.com/paperclips/index2.html\n- **Tags**: \"multi-turn\", \"agent\", \"game\"\n\n### Datasets\n- **Primary dataset(s)**: Nonne\n- **Source links**: NA\n- **Split sizes**: NA\n\n### Task\n- **Type**: multi-turn\n- **Parser**: XMLParser\n- **Rubric overview**: \n\n### Quickstart\nRun an evaluation with default settings:\n\n```bash\nuv run vf-eval paperclips\n```\n\nConfigure model and sampling:\n\n```bash\nuv run vf-eval paperclips   -m gpt-4.1-mini   -n 20 -r 3 -t 1024 -T 0.7   -a '{\"key\": \"value\"}'  # env-specific args as JSON\n```\n\nNotes:\n- Use `-a` / `--env-args` to pass environment-specific configuration as a JSON object.\n\n### Environment Arguments\nDocument any supported environment arguments and their meaning. Example:\n\n| Arg | Type | Default | Description |\n| --- | ---- | ------- | ----------- |\n| `num_trajectories` | int | `\"1\"` | Number of episodes/trajectories you wanna generate |\n\n### Metrics\nSummarize key metrics your rubric emits and how they’re interpreted.\n\n| Metric | Meaning |\n| ------ | ------- |\n| `reward` | Main scalar reward (weighted sum of criteria) |\n\n","encoding":"utf-8","truncated":false,"total_bytes":1266},"status":null}