nemotron-3-5-lightning-text2sql-lora

Run the Nemotron-3.5 Lightning Text2SQL LoRA fine-tuning tutorial (NeMo Megatron-Bridge) end-to-end for the user on a single node: data prep, checkpoint conversion, LoRA fine-tuning of the 30B-A3B hybrid Mamba-Transformer MoE, and merging the adapter back to a Hugging Face checkpoint. Use when the user wants to run this cookbook, fine-tune Nemotron-3.5 Lightning with LoRA, or adapt the notebook to their own machine.

Quality

85%

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Securityby

Low

Low-risk findings worth noting

Quality

Content

77%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, dense runbook with a clear sequenced workflow and strong per-step validation. It is slightly chatty in places and leans on the (currently absent) notebook for executable detail rather than inlining key commands.

Suggestions

Inline the exact `docker run` invocation and the Configuration cell's key fields so the skill is executable without opening the notebook.

Trim editorial asides like 'this is the single most useful thing to know when planning the run' to tighten token efficiency.

Ship the referenced `mbridge_lora_cookbook.ipynb` in the bundle (or add a references/ file) so the one-level-deep pointer resolves to a real file.

Dimension	Reasoning	Score
Conciseness	Mostly lean and information-dense — the GPU table, env-var list, and friction notes all earn their place — with only minor chattiness ('this is the single most useful thing to know when planning the run').	4 / 5
Actionability	Concrete env vars, file paths, and per-step verification criteria, but execution leans on the bundled notebook ('Use the docker run invocation in the notebook's first cell') rather than copy-paste-ready commands.	4 / 5
Workflow Clarity	Four steps are explicitly sequenced with a per-step sanity-check checkpoint and a dedicated 'Verifying success per step' section giving exact success criteria and failure-triage guidance.	5 / 5
Progressive Disclosure	Well-organized into clear single-level sections with the bundled notebook referenced one level deep; however no reference/scripts/assets bundle is present and the referenced notebook file is not in the directory, a minor organization gap.	4 / 5
	Total	17 / 20 Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description that clearly states both what the skill does and when to use it, with concrete pipeline actions and a narrow, low-conflict niche. Trigger coverage is good but could add a couple more natural synonyms.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete pipeline actions — 'data prep, checkpoint conversion, LoRA fine-tuning ... and merging the adapter back to a Hugging Face checkpoint' — giving comprehensive coverage of the workflow.	5 / 5
Completeness	Explicitly answers both what (the four pipeline stages) and when ('Use when the user wants to run this cookbook, fine-tune ... or adapt the notebook') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Good natural triggers ('run this cookbook', 'fine-tune Nemotron-3.5 Lightning with LoRA', 'adapt the notebook'), but a few common variants (e.g. 'Text2SQL', 'Mamba') are absent from the trigger clause.	4 / 5
Distinctiveness Conflict Risk	A very specific niche (Nemotron-3.5 Lightning Text2SQL LoRA on Megatron-Bridge) with distinct triggers and minimal overlap with other skills.	5 / 5
	Total	19 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: NVIDIA-NeMo/Nemotron
Path: usage-cookbook/Nemotron-3.5-Lightning/lora-text2sql/nemo-megatron-bridge/SKILL.md
Commit: 907d408

Reviewed: 6 days ago

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