"Select PINTO_model_zoo models by task family, model
Scanned 9/8/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill model-catalog --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: model-catalog
description: "Select PINTO_model_zoo models by task family, model
number/directory/name, format flags, and remarks without reopening source
evidence."
disable-model-invocation: true
metadata:
disco-role: operating
license: MIT
---
# Model Catalog
Use this sub-skill when the task is to shortlist a model from the bundled catalog, interpret format flags, or map a loose request like `ONNX hand pose` or `132_YOLOX` to a concrete folder.
## Fast route
1. Check the license gate first: do not recommend a model for use, redistribution, or execution until the target folder's license terms are acceptable.
2. Query the bundled helper for a short list:
```bash
python ../../scripts/query_model_catalog.py --category "2D/3D Hand Detection" --format ONNX
python ../../scripts/query_model_catalog.py --format OV --contains pose
python ../../scripts/query_model_catalog.py --number 132
python ../../scripts/query_model_catalog.py --directory 132_YOLOX
python ../../scripts/query_model_catalog.py --list-formats
```
3. Read [references/catalog-selection.md](references/catalog-selection.md) for category, flag, directory, name, and remark semantics.
4. Read [references/troubleshooting.md](references/troubleshooting.md) when a filter returns no match, a folder number is ambiguous, a backend flag does not fit the target runtime, or the remarks imply a resolution/input constraint.
5. Hand off to `../model-acquisition/` for downloads and artifact handling, `../inference-demos/` for running an existing model, or `../conversion-and-deployment/` for format conversion, quantization, or deployment planning.
## Boundary with sibling sub-skills
- Need to find or rank candidates only -> stay here.
- Need download scripts, artifact acquisition, or cookie/network planning -> `../model-acquisition/`.
- Need to run an existing demo/test script or interpret runtime output -> `../inference-demos/`.
- Need to convert, quantize, export, or deploy a model artifact -> `../conversion-and-deployment/`.
## What stays here
- catalog lookup and shortlist generation
- format legend interpretation
- no-network model selection
- resolution/shape hint reading from remarks
- number/directory/name mapping
## Bundled files
- [references/model-catalog.json](../../references/model-catalog.json) — the self-contained catalog data.
- [references/catalog-selection.md](references/catalog-selection.md) — selection rules, filter examples, and flag meanings.
- [references/troubleshooting.md](references/troubleshooting.md) — common failure modes and recovery steps.
- [../../scripts/query_model_catalog.py](../../scripts/query_model_catalog.py) — offline query helper for the bundled catalog.

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