pytorch-lightning

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

Quality

81%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

72%

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

A highly actionable, well-structured skill body with executable examples and clean progressive disclosure. It is held back by marketing/time-sensitive padding and the absence of explicit validation checkpoints in its training workflows.

Suggestions

Remove marketing fluff and time-sensitive claims (e.g., '⭐ 29,000+', '1M+ downloads/month, battle-tested', 'Used by: Kaggle winners', 'That's it!') to tighten conciseness and avoid stale version/star counts.

Add explicit validation checkpoints to the workflows (e.g., confirm the training run starts, assert a checkpoint file exists after fit) to support error recovery and lift workflow clarity.

Trim the 'Key advantages' and 'When to use vs alternatives' sections to essential decision criteria, moving deeper comparison detail into a reference file.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient code, but it carries marketing fluff and time-sensitive claims ('⭐ 29,000+', '1M+ downloads/month, battle-tested', 'Used by: Kaggle winners', 'That's it!') that add tokens without aiding execution.	2 / 3
Actionability	Multiple complete, executable code blocks with real imports and copy-paste-ready Trainer/LightningModule examples match the top anchor for concrete, runnable guidance.	3 / 3
Workflow Clarity	Steps are clearly sequenced ('Convert PyTorch to Lightning (3 steps)', numbered workflows), but there are no explicit validation checkpoints or validate-then-proceed feedback loops, leaving checkpoints implicit.	2 / 3
Progressive Disclosure	The body is a concise overview that signals one-level-deep references to real bundle files ([references/callbacks.md], [references/distributed.md], [references/hyperparameter-tuning.md]), splitting advanced topics cleanly.	3 / 3
	Total	10 / 12 Passed

Description

90%

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 with explicit 'what' and 'when' guidance and good trigger-term coverage. The only blemish is the second-person 'you want' phrasing, which the rubric penalizes on specificity.

Dimension	Reasoning	Score
Specificity	The description lists multiple concrete features ('Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate') which would merit a 3, but the second-person phrasing 'Use when you want clean training loops' incurs the rubric's -1 specificity penalty.	2 / 3
Completeness	It explicitly answers both 'what' (Trainer class, distributed training, callbacks, minimal boilerplate) and 'when' via the explicit 'Use when you want clean training loops with built-in best practices' trigger clause.	3 / 3
Trigger Term Quality	Natural user-facing terms are well covered ('PyTorch', 'training loops', 'distributed training', 'DDP/FSDP/DeepSpeed', 'best practices'), matching the top anchor for terms users would actually say.	3 / 3
Distinctiveness Conflict Risk	PyTorch Lightning occupies a clear niche with distinct triggers (training loops, DDP/FSDP/DeepSpeed) that are unlikely to fire for unrelated skills.	3 / 3
	Total	11 / 12 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: synthetic-sciences/openscience
Path: backend/cli/skills/ml-training/pytorch-lightning/SKILL.md
Commit: 52845c3

Reviewed: about 13 hours ago

Table of Contents

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