---

name: extensions description: "Custom hls4ml layer, parser handler, template, optimizer-flow, and backend/writer plugin workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Extensions

Use this sub-skill for extension tasks around hls4ml internals:

• custom Keras, PyTorch, or ONNX layer support
• IR layer classes and attribute/weight wiring
• backend templates and custom source registration
• optimizer passes, flows, and pass membership checks
• external backend or writer plugins
• diagnosing missing handlers, plugin discovery, or flow wiring

Do not use this sub-skill for ordinary model conversion, vendor synthesis, or precision/resource tuning. Route those to the sibling frontends, backends, or analysis sub-skills.

Operating map

1. Identify the extension surface: parser handler, IR layer, template/source, optimizer pass, or backend plugin.
2. Read the matching reference:
   • references/extension-api.md
   • references/plugins.md
   • references/custom-layer-checklist.md
   • references/troubleshooting.md
3. Run scripts/inspect_plugins.py when you need a safe, non-loading discovery probe.
4. If you add behavior, pair it with a focused test that proves registration, flow reachability, and a small compile/predict smoke when appropriate.

Fast routing

• Custom layer implementation or parser handler -> references/extension-api.md
• Plugin or backend visibility problem -> references/plugins.md
• Implementation checklist and test planning -> references/custom-layer-checklist.md
• Missing source, pass, or registration failure -> references/troubleshooting.md

Safe inspection

python scripts/inspect_plugins.py

The script only reports discovery metadata. It does not import plugin modules.