volcano-plot-script
Generate R/Python code for volcano plots from DEG (Differentially Expressed Genes) analysis results. Triggered when user needs visualization of gene expression data, p-value vs fold-change scatter plots, publication-ready figures for bioinformatics analysis.
Install with Tessl CLI
npx tessl i github:aipoch/medical-research-skills --skill volcano-plot-script62
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that excels across all dimensions. It clearly specifies the concrete output (R/Python code for volcano plots), uses domain-appropriate trigger terms that bioinformatics users would naturally employ, and explicitly states both what the skill does and when to use it. The specialized domain (DEG analysis, volcano plots) makes it highly distinctive with minimal conflict risk.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists specific concrete actions: 'Generate R/Python code for volcano plots from DEG analysis results' clearly describes the output (code), the visualization type (volcano plots), and the input data (DEG analysis results). | 3 / 3 |
Completeness | Clearly answers both what ('Generate R/Python code for volcano plots from DEG analysis results') and when ('Triggered when user needs visualization of gene expression data, p-value vs fold-change scatter plots, publication-ready figures for bioinformatics analysis'). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'volcano plots', 'DEG', 'Differentially Expressed Genes', 'gene expression data', 'p-value vs fold-change', 'publication-ready figures', 'bioinformatics analysis' - these are all terms bioinformatics users naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche - volcano plots for DEG analysis is a very specific bioinformatics visualization task. The combination of 'volcano plots', 'DEG', 'fold-change', and 'gene expression' creates clear, non-conflicting triggers unlikely to overlap with general data visualization skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
7%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is essentially a documentation template rather than actionable guidance. It extensively describes metadata, risk assessments, and evaluation criteria that Claude doesn't need, while completely omitting the core content: actual Python/R code for generating volcano plots. The skill fails its primary purpose of teaching Claude how to generate volcano plot scripts.
Suggestions
Replace the verbose overview and use case sections with actual executable Python and R code examples for generating volcano plots (e.g., complete matplotlib/ggplot2 implementations)
Remove administrative sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status) that don't help Claude generate plots
Add a clear workflow: 1) Load DEG data, 2) Apply thresholds, 3) Generate plot with specific code, 4) Customize labels/colors
Include at least one complete, copy-paste ready script that produces a publication-quality volcano plot from sample input
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive sections Claude doesn't need (Risk Assessment tables, Security Checklists, Evaluation Criteria, Lifecycle Status). Explains basic concepts like what volcano plots are and DEG analysis concepts that Claude already knows. The actual actionable content is buried under administrative overhead. | 1 / 3 |
Actionability | Despite being a 'script generator' skill, there is no actual executable code for generating volcano plots. The only code shown is a CLI invocation example, not the actual plotting code. No Python or R examples of the actual visualization logic are provided. | 1 / 3 |
Workflow Clarity | No clear workflow for generating volcano plots. The skill describes what it does but never shows how to actually create the plots. Missing steps for data loading, plot generation, customization, and validation of output quality. | 1 / 3 |
Progressive Disclosure | References to external files exist (references/, requirements.txt, scripts/main.py) but the core content that should be in SKILL.md (actual plotting code and workflow) is missing entirely. Structure exists but content is misallocated - administrative sections are inline while essential code is absent. | 2 / 3 |
Total | 5 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Reviewed
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