{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "makezur-agenticstar--run-garden-shears-example",
 "repo": "makezur/agenticSTAR",
 "repo_url": "https://github.com/makezur/agenticSTAR",
 "repo_slug": "makezur-agenticstar",
 "title": "Reconstruct the garden shears example end to end",
 "page_title": "How to reconstruct the garden shears example end to end with Agentic STAR",
 "summary": "Run one supervised agent session on the committed example and get a GLB and pose.json.",
 "who": "A researcher or engineer who wants to see the full pipeline work on a known capture before using their own video.",
 "problem": "Setting up an agentic reconstruction harness is hard to judge without seeing a complete run on known data.",
 "outcome": "A runs/ directory containing scene.py, mesh/object.glb, mesh/pose.json and per-pass renders under iterations/.",
 "steps": [
  "Run `./install.sh` to build the artscript env, Blender 4.2.5 and the pi3x env.",
  "Run `export ANTHROPIC_API_KEY=sk-ant-...` in the shell you will use.",
  "Run `tools/install_claude_bwrap.sh` once so the key is stored in a state dir outside the checkout.",
  "Run `tools/run_kf.sh --agent claude --timeout-hours 4 examples/garden_shears/capture:0`.",
  "Run `tools/claude-supervisor attach --run-dir runs/capture_kf_` to watch the run."
 ],
 "agent_prompt": "In the agenticSTAR repo, set up the environment with ./install.sh and run the garden shears example with Claude Code using tools/run_kf.sh on examples/garden_shears/capture:0 on GPU 0. Expect runs/ to contain scene.py, mesh/object.glb and mesh/pose.json. Verify that mesh/pose.json holds per-frame poses and joint states before reporting success.",
 "agents": [
  "claude-code"
 ],
 "difficulty": "Advanced",
 "time": "5 hours",
 "basis": "readme",
 "caveat": "A run takes hours and many tokens, so budget for model cost and use --timeout-hours to bound it.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "python",
 "requirements": [
  "Linux x86_64 host with an NVIDIA GPU",
  "micromamba, git, curl, tar, xz, python3, tmux, bubblewrap, iproute2 and ffmpeg installed on the host",
  "Root or CAP_NET_ADMIN for the sandbox network namespace",
  "An Anthropic API key for Claude Code or an OpenAI API key for Codex",
  "claude and/or codex available on PATH"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": true,
 "score": 1.0,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/makezur-agenticstar/run-garden-shears-example/",
 "md": "https://dedupedai.com/use-cases/makezur-agenticstar/run-garden-shears-example/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/makezur-agenticstar--run-garden-shears-example.json",
 "api_version": "v1"
}