table-1-generator

Automated generation of baseline characteristics tables (Table 1) for clinical research papers.

Quality

60%

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tessl review fix ./scientific-skills/Data Analysis/table-1-generator/SKILL.md

Quality

Content

60%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 well-structured with executable commands, a clear validated workflow, and a clean one-level reference to the bundled script, but it is padded with substantial repeated and generic process boilerplate that hurts token efficiency. Consolidating the overlapping handling/checklist sections would materially raise conciseness.

Suggestions

Merge the overlapping Error Handling, Failure Handling, Output Contract, Output Requirements, and When Not to Use sections into a single concise section to remove repetition.

Cut generic boilerplate that Claude already knows (e.g. "Do not fabricate files, citations, data") and keep only skill-specific guidance.

Replace abstract workflow verbs ("Confirm the user objective", "Return a structured result") with concrete, script-anchored steps tied to scripts/main.py.

Dimension	Reasoning	Score
Conciseness	The body is noticeably verbose, repeating the same guidance across overlapping sections (Error Handling, Failure Handling, Output Contract, Output Requirements, When Not to Use) and padding with generic process boilerplate Claude already knows, fitting the "noticeably verbose; several unnecessary padded sections" anchor.	2 / 5
Actionability	It provides copy-paste-ready commands ("python scripts/main.py --data patients.csv --group treatment --output table1.csv", py_compile, --help) and a concrete parameter table, with only minor gaps in the surrounding abstract guidance.	4 / 5
Workflow Clarity	The Workflow lists a clear 5-step sequence with explicit validation ("stop early if the task would require unsupported assumptions") and a feedback/fallback loop ("If execution fails... switch to the fallback path"), with only minor checkpoint gaps keeping it below a 5.	4 / 5
Progressive Disclosure	The bundle is a single real file (scripts/main.py) referenced one level deep and verifiable, sections are organized with headers, and there is no nested reference chain; the main gap is inlined generic boilerplate that could be trimmed.	4 / 5
	Total	14 / 20 Passed

Description

61%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 to a clear clinical-research niche and uses natural trigger terms, but it only states a single action and lacks any explicit "when to use" trigger guidance. Adding a Use-when clause and one or two more concrete actions would lift completeness and specificity.

Suggestions

Add an explicit trigger clause, e.g. "Use when generating Table 1 / baseline-characteristics summaries for clinical research papers."

Expand the action list beyond "generation" to concrete operations like variable-type detection, group comparisons, and APA-formatted output.

Include common synonyms/extensions users might say (e.g. "baseline table", "demographics table", ".csv") to improve trigger coverage.

Dimension	Reasoning	Score
Specificity	"Automated generation of baseline characteristics tables (Table 1)" names a specific domain and one concrete action (generating tables), but lists only that single action rather than comprehensive coverage, matching the anchor for naming a domain plus 1-2 actions.	3 / 5
Completeness	It gives a clear "what" (automated generation of Table 1) but entirely omits any "Use when..." / trigger clause; per the rubric guideline a missing explicit trigger caps completeness at 3.	3 / 5
Trigger Term Quality	"baseline characteristics tables (Table 1)" and "clinical research papers" are natural terms researchers actually say, giving good keyword coverage; it stops short of comprehensive synonyms/extensions, so it is above the midpoint but not a 5.	4 / 5
Distinctiveness Conflict Risk	The niche (Table 1 baseline-characteristics generation for clinical research) is mostly distinct with minor overlap risk against general statistics skills, but the absence of an explicit trigger phrase keeps it just below a 5.	4 / 5
	Total	14 / 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: scientific-skills/Data Analysis/table-1-generator/SKILL.md
Commit: f5ef65b

Reviewed: ~10 hours ago

Table of Contents

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