code-refactor-for-reproducibility

Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications.

Quality

72%

Does it follow best practices?

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Securityby

Passed

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Fix and improve this skill with Tessl

tessl review fix ./scientific-skills/Data Analysis/code-refactor-for-reproducibility/SKILL.md

Quality

Content

52%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 content offers strong, executable examples and a clearly sequenced validation workflow, but it is padded with redundant template material and — critically — references multiple reference files that do not exist in the bundle. Fixing the dangling references and trimming the boilerplate would markedly improve it.

Suggestions

Create the referenced files (references/environment-setup.md, references/guide.md, references/examples/, references/api-docs/) or remove the dangling references so navigation is not broken.

Delete the verbatim re-pastes of the frontmatter description in 'When to Use' and 'Key Features' and the generic 'Output Requirements'/'Response Template'/'Input Validation' boilerplate to recover token budget.

Move the large Step 2 and Step 3 code blocks into the reference files, keeping only concise illustrative snippets inline, so SKILL.md acts as an overview rather than a monolith.

Dimension	Reasoning	Score
Conciseness	The full frontmatter description is pasted verbatim twice in the body ('When to Use', 'Key Features'), and generic template sections like 'Output Requirements', 'Response Template', and 'Input Validation' add padding without new instruction.	2 / 5
Actionability	Provides several concrete, executable examples — AST-based hardcoded-path detection, docstring refactor, argparse parameterization, seed setting, and checksum-based reproducibility checks — with only minor gaps.	4 / 5
Workflow Clarity	Steps 1–5 are clearly sequenced and Step 5 includes explicit validation checkpoints (checksum diff, double-run determinism, a reproducibility checklist), with only minor gaps around pre-apply validation in Step 2.	4 / 5
Progressive Disclosure	The body points to references/environment-setup.md, references/guide.md, references/examples/, and references/api-docs/, but none of these files exist in the bundle — references are broken — and large inline code blocks that belong in separate files are not split out.	2 / 5
	Total	12 / 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.

The description is concrete, complete, and well-scoped to a distinct niche, covering both the trigger conditions and the specific transformations performed. Its only mild weakness is trigger-term breadth, lacking synonyms or file extensions users might naturally say.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility' — with comprehensive coverage of the domain.	5 / 5
Completeness	Explicitly answers both: an explicit 'Use when...' trigger clause and a clear 'what' (transforms research code, adds documentation, implements error handling, creates environment specs).	5 / 5
Trigger Term Quality	Strong natural phrases like 'refactoring research code for publication', 'reproducible computational workflows', and 'sharing with collaborators', but missing common synonyms or file extensions a user might say.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche — publication-ready reproducible research code refactoring — with distinct triggers and minimal overlap risk against general coding skills.	5 / 5
	Total	19 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
referenced_paths_exist	Referenced path issues: 5 missing	Warning

	Total	14 / 16 Passed

Repository: aipoch/medical-research-skills
Path: scientific-skills/Data Analysis/code-refactor-for-reproducibility/SKILL.md
Commit: f5ef65b

Reviewed: 25 minutes ago

Table of Contents

Discovery Implementation Validation

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