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pytorch-fsdp

Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2

41

Quality

52%

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tessl review fix ./cli-tool/components/skills/ai-research/distributed-training-pytorch-fsdp/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

17%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.

The body is an auto-generated scrape dump rather than a usable skill: massive inlined API reference material, dangling code fences containing single words, and boilerplate sections referencing files and directories that do not exist. Almost nothing guides a user through actually implementing FSDP training. It needs a complete restructuring around concise instructions with details pushed into the references bundle.

Suggestions

Replace the inlined 'Common Patterns' doc dumps with a short overview that moves the scraped documentation into the existing references/ files and points to them explicitly by path.

Remove pointers to nonexistent files ('getting_started', 'tutorials', 'api', 'guides') and the placeholder scripts/ and assets/ boilerplate sections, keeping only references that actually exist (index.md, other.md).

Add a concise, sequenced getting-started workflow (e.g., init process group -> wrap model with FullyShardedDataParallel -> configure sharding/mixed precision -> verify with a small run) with executable, copy-paste-ready code.

DimensionReasoningScore

Conciseness

The body is ~160K characters of scraped PyTorch documentation inlined into SKILL.md (one 'Pattern' is a single 130K-char line reproducing the entire torch.distributed API reference), extensively explaining concepts Claude already knows. This is the 'severely verbose; heavily padded' anchor — it cannot be 2 because the padding is not a few unnecessary sections but nearly the whole body.

1 / 5

Actionability

Real executable code exists (e.g., the init_device_mesh and Join examples), but it is embedded in raw doc dumps with no instruction on how to actually set up or run FSDP training. Guidance like 'Start with the getting_started or tutorials reference files' is a high-level hint pointing at files that do not exist, fitting 'minimal concrete guidance; missing the specific steps to execute'.

2 / 5

Workflow Clarity

A rough usage sequence exists ('For Beginners start with getting_started... For Specific Features use the category file... For Code Examples see the quick reference'), but it is vague, references nonexistent files, and has no validation checkpoints or error-recovery loops. Not 1 because some sequence is present; not 3 because the sequence is broken rather than merely missing checkpoints.

2 / 5

Progressive Disclosure

Content that clearly belongs in separate reference files (the full torch.distributed API dump and other scraped pages) is inlined monolithically into SKILL.md, matching 'content that clearly belongs in separate files is inlined'. The references/ bundle (index.md, other.md) exists but is only pointed to with a vague one-line label ('other.md - Other documentation'), and the body additionally cites nonexistent files and placeholder scripts/ and assets/ sections.

2 / 5

Total

7

/

20

Passed

Description

66%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.

The description is specific and reasonably distinctive, naming concrete FSDP capabilities with natural trigger terms. Its main weakness is the complete absence of a 'Use when...' clause, which both caps completeness and weakens trigger guidance. Adding an explicit trigger sentence with synonyms (e.g., distributed training, sharded training) would raise it substantially.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user asks about FSDP, Fully Sharded Data Parallel, sharded model training, or distributed training with PyTorch.'

Include common user phrasings and synonyms such as 'distributed training', 'sharding', and 'torch.distributed' alongside the existing FSDP-specific terms.

Phrase capabilities as actions (e.g., 'Configure parameter sharding, mixed precision, and CPU offloading for PyTorch training') rather than topic nouns.

DimensionReasoningScore

Specificity

Lists several specific concrete capabilities ("parameter sharding, mixed precision, CPU offloading, FSDP2") beyond just naming the domain, matching the 'several specific actions; minor gaps' anchor. Not 5 because the items are topic nouns rather than explicit actions and coverage gaps exist (e.g., wrapping strategies, checkpointing); not 3 because it goes well beyond 1-2 concrete items.

4 / 5

Completeness

Has a clear 'what' ("Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP") but no 'Use when...' clause or equivalent trigger guidance, capping completeness at 3 per the judging guidelines. Not 4 because the 'when' is entirely absent rather than just implicit; not 2 because the 'what' is specific and concrete.

3 / 5

Trigger Term Quality

"PyTorch FSDP", "Fully Sharded Data Parallel", "mixed precision", "CPU offloading", "FSDP2" are natural terms users would say when needing this skill. Not 5 because common variations like "distributed training", "sharded training", or "torch.distributed" are absent; not 3 because keyword coverage is good and specific, not partial.

4 / 5

Distinctiveness Conflict Risk

"PyTorch FSDP" and "FSDP2" establish a clear niche with distinct triggers, but "mixed precision" and "CPU offloading" create minor overlap risk with general distributed-training or memory-optimization skills. Fits 'mostly distinct; minor overlap risk with closely related skills' better than the fully-distinct 5 anchor.

4 / 5

Total

15

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

davila7/claude-code-templates

Path

cli-tool/components/skills/ai-research/distributed-training-pytorch-fsdp/SKILL.md

Reviewed

Table of Contents

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