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survival-analysis-km

Kaplan-Meier survival analysis tool for clinical and biological research. Generates publication-ready survival curves with statistical tests.

46

Quality

50%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./scientific-skills/Data Analysis/survival-analysis-km/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

38%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 long and boilerplate-heavy, re-explains statistical concepts Claude already knows, and ships broken cross-references plus references to non-existent bundle files. Concrete argument/usage tables provide some actionability, but corrupted parameter tables and commented-only examples leave guidance incomplete.

Suggestions

Remove the generic boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status, Output Contract) and the re-explanation of KM/log-rank/Cox basics to cut the body to a lean overview.

Fix the duplicate/corrupted Parameters table (empty descriptions, `--figsize` str '10', `--risk-table` Required vs Optional) and provide a real, runnable example command instead of commented `# Example invocation` lines.

Resolve the broken 'See `## X` above' pointers (Features/Usage/Workflow appear below, not above) and either ship the referenced `scripts/main.py` and `references/` or stop pointing to them.

DimensionReasoningScore

Conciseness

At ~320 lines the body is padded with generic boilerplate (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status, Output Contract, etc.) and re-explains concepts Claude already knows (KM estimator, log-rank, Cox model), with several duplicated/broken 'See ## X above' pointers — matches 'noticeably verbose; several unnecessary explanations or padded sections'.

2 / 5

Actionability

There are concrete argument tables and example invocations, but the runnable examples are only commented `# Example invocation` lines, the duplicate Parameters table is corrupted (empty descriptions, `--figsize` str '10', `--risk-table` listed Required), and the referenced `scripts/main.py` does not exist — concrete but incomplete.

3 / 5

Workflow Clarity

Two competing workflow lists exist with a py_compile validation checkpoint and a fallback path, but steps are generic and duplicated, cross-references are broken, and validation is implicit rather than a tight validate→fix→retry loop.

3 / 5

Progressive Disclosure

The body points to `scripts/main.py` and `references/` for papers, datasets, and guidelines, but neither bundle directory exists, and navigation is broken ('See `## Features` above' when Features is below) — references are non-functional and much generic content is inlined.

2 / 5

Total

10

/

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 clearly names a specific niche and a couple of concrete actions but lacks an explicit 'Use when' trigger clause, which caps completeness. It is distinctive and uses natural terminology, though keyword coverage stops short of synonyms and file extensions.

Suggestions

Add an explicit 'Use when...' clause naming concrete triggers (e.g. survival analysis, time-to-event data, censoring, log-rank comparison) to raise completeness above 3.

Include natural synonyms and file extensions users mention (CSV, .csv, censored data, log-rank test) to push trigger term coverage toward 5.

Add one or two more concrete capabilities (hazard ratios, risk tables, median survival) so specificity reaches comprehensive coverage.

DimensionReasoningScore

Specificity

Names the domain ('Kaplan-Meier survival analysis tool for clinical and biological research') and 1-2 concrete actions ('Generates publication-ready survival curves with statistical tests'), but coverage is not comprehensive — matches the 'names domain and 1-2 concrete actions' anchor rather than the broader 4.

3 / 5

Completeness

Has a clear 'what' but no explicit 'Use when...' trigger clause; per the rubric a missing explicit trigger guidance caps completeness at 3, and 'when' is only weakly implied.

3 / 5

Trigger Term Quality

Includes natural terms researchers actually say ('survival analysis', 'Kaplan-Meier', 'survival curves', 'statistical tests', 'clinical and biological research'); a few natural synonyms and file extensions (e.g. CSV, censoring, log-rank) are missing, so it sits at good-but-not-comprehensive coverage.

4 / 5

Distinctiveness Conflict Risk

'Kaplan-Meier survival analysis' is a clear, narrow statistical niche with distinct triggers and minimal overlap risk; the trailing 'with statistical tests' is slightly generic, keeping it just below a 5.

4 / 5

Total

14

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

referenced_paths_exist

Referenced path issues: 12 missing

Warning

Total

14

/

16

Passed

Repository
aipoch/medical-research-skills
Reviewed

Table of Contents

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