tao-run-automl-deft-pipeline SKILL.md skillA
tao-run-automl-deft-pipeline from nvidia-tao/tao-skill-bank is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add nvidia-tao/tao-skill-bank/tao-run-automl-deft-pipeline@v0.1.0Pins v0.1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- nvidia-tao/tao-skill-bank
- Path
skills/applications/tao-run-automl-deft-pipeline/SKILL.md- Versions recorded
- 5
- Latest version
- v0.1.0, committed Aug 10, 2026
- First version recorded
- Jun 3, 2026
- Size
- 17,494 bytes
- Repository stars
- 95
- License
- Apache-2.0
Run the canonical NVIDIA AOI three-phase training pipeline — Phase 1 AutoML baseline (HPO), Phase 2 DEFT loop (RCA → SDG → mining → plain-train retrain), Phase 3 AutoML refinement on the DEFT-augmented dataset. Use when the user asks to "run the AOI workflow", "fine-tune my PCB AOI model end-to-end", "improve my AOI ChangeNet model", or "AOI workflow with AutoML" request — route here instead of tao-run-deft-aoi directly unless the user explicitly asks for the DEFT loop ONLY (e.g.…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# AutoML + DEFT Pipeline
A workflow-bridge skill that runs **three phases** in sequence by delegating to two existing skills — `tao-run-automl` for HPO and a DEFT application skill (default `tao-run-deft-aoi` for AOI; other `skills/applications/deft-*` skills for non-AOI cases) for the iterative data-improvement loop.
This skill **does not** re-implement AutoML or DEFT. It owns only the connective tissue: HPO spec inputs, the spec-handoff between AutoML and DEFT, and the post-DEFT AutoML re-run on the augmented dataset.
## Routing policy
- User asks to "run the AOI workflow" or "improve my AOI ChangeNet model" — **default to this skill**, not `tao-run-deft-aoi` directly. The bare DEFT loop is the inner stage of this pipeline.
- User wants AutoML and DEFT chained on the same model/dataset
- User says "AutoML at both ends", "tune HPs then DEFT", "warm-start DEFT", "AutoML before and after DEFT"
- User has an AutoML-tuned spec and asks how to feed it into DEFT
## When this skill does NOT apply
- User explicitly asks for the DEFT loop only ("run JUST the DEFT loop", "skip AutoML") → use `tao-run-deft-aoi` directly
…Read the whole file at its exact version.
How to install
mdr add nvidia-tao/tao-skill-bank/tao-run-automl-deft-pipeline@sha256:abe493b6d3e4b596The line at the top of this page pins the label v0.1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_ieazvfvrwcxlfpki)
2 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 5 versions of this file, between Jun 3, 2026 and Aug 10, 2026, about one every 17 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v0.1.0 latest | 2026-08-10 | 37f98c1 | 17,494 B | A | view · diff |
| v0.1.0 | 2026-06-22 | b95c878 | 17,586 B | A | view · diff |
| v0.4.0 | 2026-06-08 | 05799a1 | 17,738 B | A | view · diff |
| v0.4 | 2026-06-03 | 94ef697 | 30,502 B | A | view · diff |
| v0.4 | 2026-06-03 | 2fd0a48 | 30,453 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (17494 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
nvidia-tao/tao-skill-bank · 95 stars · license Apache-2.0 · pushed 2026-10-21 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_ieazvfvrwcxlfpki GET https://markdownregistry.com/api/v1/resolve?ref=nvidia-tao/tao-skill-bank/tao-run-automl-deft-pipeline GET https://markdownregistry.com/api/v1/blob/abe493b6d3e4b59680088bfe65d2d5728af216cc0163d1d5f4a0de39d92c68e7
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.