lightgbm-analysis

Use when training a LightGBM model on tabular data in R and returning model metrics, feature importance ranking tables, and feature importance plots.

Quality

83%

Does it follow best practices?

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Securityby

Passed

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Quality

Content

73%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, highly actionable CLI skill with clear workflows and validation feedback loops. Its main weaknesses are redundancy across the output/contract/validation sections and several examples and a reference table pointing to bundled test data that is absent from the bundle.

Suggestions

Consolidate the output-file list into one place (e.g. Outputs) and have Success And Failure Contract, Validation, and Common Errors reference it instead of re-listing the same files.

Bundle the tests/data/ sample files (dt_sample1.csv, dt_sample2.csv, dt_sample3.txt) or remove the tests/data/ row from 'Read These Files When Needed' so every referenced path resolves.

Trim the seven Quick Examples to the smoke test plus one binary and one regression preset, linking references/cli-guide.md for the remaining variants.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient reference material, but the same output-file list recurs across Outputs, Success And Failure Contract, Validation, and Common Errors, and seven near-identical example blocks add padding that could be trimmed.	3 / 5
Actionability	Commands are concrete and copy-paste ready across binary/regression/split/txt cases, but every example references tests/data files (dt_sample1.csv, dt_sample3.txt, etc.) that are not present in the bundle, a minor executability gap.	4 / 5
Workflow Clarity	A 7-step Minimal Workflow is paired with an explicit Success/Failure Contract, a Validation section with file-existence checks, and Caution Remediation feedback loops mapping each failure mode to a rerun change.	5 / 5
Progressive Disclosure	A need-based 'Read These Files When Needed' table gives one-level-deep navigation to real references (algorithm.md, cli-guide.md, troubleshooting.md, main.R), but it also lists tests/data/ which does not exist in the bundle.	4 / 5
	Total	16 / 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, concrete description that explicitly covers both what the skill does and when to use it in third-person voice. Keyword coverage is good but could add synonyms (GBM, gradient boosting) to reach full trigger-term comprehensiveness.

Dimension	Reasoning	Score
Specificity	Names the domain (LightGBM, tabular data, R) and lists multiple concrete actions—training a model and returning metrics, feature-importance ranking tables, and plots—matching the comprehensive-coverage anchor.	5 / 5
Completeness	Explicitly answers both what (train a LightGBM model and return metrics/tables/plots) and when ('Use when training a LightGBM model on tabular data in R') with a concrete trigger phrase.	5 / 5
Trigger Term Quality	Includes natural terms a user would say (LightGBM, tabular data, R, feature importance, model metrics, plots), but omits common synonyms (gradient boosting, GBM) and file extensions, leaving a few natural terms missing.	4 / 5
Distinctiveness Conflict Risk	LightGBM modeling in R producing feature-importance rankings is a clear, narrow niche with distinct triggers and minimal overlap risk with other skills.	5 / 5
	Total	19 / 20 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: aipoch/medical-research-skills
Path: awesome-med-research-skills/Data Analysis/LightGBM-analysis/SKILL.md
Commit: f5ef65b

Reviewed: ~9 hours ago

Table of Contents

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