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Asset Retrieval

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asset-retrieval

Asset Retrieval is an Agent Skill for documents published in the HorizonRobotics/EmbodiedGen repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Retrieve existing EmbodiedGen assets from a configurable dataset index CSV by natural-language descriptions and return matching `.urdf` paths. Use when users describe an asset they want, ask to find one or several existing URDF assets, or need a fast lookup over the local asset index instead of scanning folders manually.

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How to use this skill

Bring this guide into your coding agent with a prompt tailored to the tool you use.

  1. Open your project in Codex.
  2. Copy and paste the prompt below.
  3. Review files and risks before approving any action.
Prompt to paste
Inspect the Agent Skill at https://github.com/HorizonRobotics/EmbodiedGen/blob/HEAD/embodied_gen/skills/asset-retrieval/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/asset-retrieval, but wait for my approval before writing files or running scripts.

Copying this prompt does not install or run the skill. Review third-party files before use.

Asset Retrieval

Look up simulation-ready assets from dataset_index.csv and return .urdf paths. The CSV index is the single source of truth.

Workflow

Preferred — agent reads CSV directly:

  1. Read dataset_index.csv into context.
  2. Semantically match the user's description (open-ended, fuzzy, or in any language) against category, secondary_category, primary_category, and description columns.
  3. Return the best-matching absolute .urdf path; return multiple candidates when the request is broad or explicitly asks for several.
  4. Briefly explain why the returned asset matches.

This path handles open-ended queries like "a tall chair suitable for a coffee shop" or "能放在客厅角落的落地灯" that pure keyword matching cannot resolve.

Fallback — CLI script (no network / no LLM):

When the agent is unavailable, use the helper script which performs offline keyword-based ranking:

python embodied_gen/skills/asset-retrieval/scripts/retrieve_asset.py \
  "modern dining chair curved backrest"

For the CLI path, rewrite open-ended or Chinese descriptions into compact English keywords first (e.g. 能放在客厅角落的落地灯 → floor lamp).

Index Resolution

Checked in order — first match wins:

  1. --index-file CLI argument
  2. $EMBODIEDGEN_DATASET_INDEX environment variable
  3. $EMBODIEDGEN_DATASET_ROOT/dataset_index.csv
  4. <repo-root>/outputs/EmbodiedGenData/dataset/dataset_index.csv

Dataset root follows a parallel order (--dataset-root → $EMBODIEDGEN_DATASET_ROOT → repo default).

Required CSV Columns

uuid, primary_category, secondary_category, category, description, generate_time, urdf_path

Query Guidelines

  • Use explicit object words: chair, bar stool, remote control.
  • Keep discriminating modifiers: wooden, orange, modern, round.
  • Open-ended or Chinese descriptions are fine for the agent path; rewrite to English keywords only when using the CLI script.

Script Usage

# Single best match (absolute path on stdout)
python embodied_gen/skills/asset-retrieval/scripts/retrieve_asset.py \
  "modern dining chair curved backrest"

# Multiple candidates with scores
python embodied_gen/skills/asset-retrieval/scripts/retrieve_asset.py \
  "orange cushioned bar stool" \
  --top-k 5 --format json

# Custom dataset location
python embodied_gen/skills/asset-retrieval/scripts/retrieve_asset.py \
  "black remote control" \
  --dataset-root /path/to/dataset \
  --index-file /path/to/dataset/dataset_index.csv

# Relative paths instead of absolute
python embodied_gen/skills/asset-retrieval/scripts/retrieve_asset.py \
  "wooden bar stool" --relative-paths

Exit code 1 with "No matching assets found." on stderr when nothing matches.