regression-analysis-helper
Regression Analysis Helper - Auto-activating skill for Data Analytics. Triggers on: regression analysis helper, regression analysis helper Part of the Data Analytics skill category.
33
0%
Does it follow best practices?
Impact
93%
0.93xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/12-data-analytics/regression-analysis-helper/SKILL.mdQuality
Discovery
0%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 description is essentially a title and category label with no substantive content. It fails to describe any concrete capabilities, lacks natural trigger terms users would use, provides no 'when to use' guidance, and offers insufficient detail to distinguish it from other data analytics skills.
Suggestions
Add specific concrete actions such as 'Fits linear and multiple regression models, calculates coefficients and R-squared values, generates residual plots, and tests for statistical significance.'
Add an explicit 'Use when...' clause with natural trigger terms like 'Use when the user asks about regression, predicting outcomes, fitting a model, correlation analysis, R-squared, coefficients, or linear/logistic regression.'
Remove the redundant repeated trigger term and replace with diverse natural keywords users would actually say, such as 'linear regression', 'predict', 'statistical model', 'OLS', 'dependent variable', etc.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description names a domain ('regression analysis') but describes no concrete actions. There are no specific capabilities listed such as 'fit linear models', 'calculate R-squared', 'generate residual plots', etc. It is essentially a title repeated with no actionable detail. | 1 / 3 |
Completeness | The description fails to answer both 'what does this do' and 'when should Claude use it'. There is no explanation of capabilities and no explicit 'Use when...' clause or equivalent trigger guidance. | 1 / 3 |
Trigger Term Quality | The only trigger term is 'regression analysis helper' repeated twice. It lacks natural keywords users would say such as 'linear regression', 'predict', 'correlation', 'fit model', 'R-squared', 'coefficients', 'OLS', or 'statistical modeling'. | 1 / 3 |
Distinctiveness Conflict Risk | While 'regression analysis' is somewhat specific, the description is so vague that it could overlap with any data analytics, statistics, or modeling skill. The generic framing ('Data Analytics skill category') increases conflict risk with other analytics-related skills. | 1 / 3 |
Total | 4 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is an empty template/placeholder with no substantive content about regression analysis. It contains only generic boilerplate text that could apply to any skill topic, with zero actionable guidance, no code examples, no statistical methods, and no real information about performing regression analysis. It provides no value beyond what the skill's title alone conveys.
Suggestions
Add concrete, executable code examples for common regression tasks (e.g., linear regression with scikit-learn or statsmodels, including data loading, model fitting, and interpreting coefficients).
Include a clear workflow for regression analysis: data exploration → assumption checking → model fitting → diagnostics (residual plots, R², p-values) → interpretation, with validation checkpoints at each stage.
Provide specific guidance on choosing regression types (linear, logistic, polynomial, ridge/lasso) based on data characteristics, with decision criteria rather than vague descriptions.
Remove all boilerplate sections (Purpose, When to Use, Example Triggers) that add no information and replace with actionable content like SQL queries for data preparation, Python code for model building, and interpretation guidelines.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is entirely filler and boilerplate. It explains nothing Claude doesn't already know, repeats the trigger phrase 'regression analysis helper' excessively, and provides zero domain-specific information about regression analysis. | 1 / 3 |
Actionability | There are no concrete steps, code examples, commands, or specific guidance. Every section is vague and abstract — 'Provides step-by-step guidance' without actually providing any steps, no executable code, no statistical methods, no library references. | 1 / 3 |
Workflow Clarity | There is no workflow whatsoever. No sequenced steps for performing regression analysis, no validation checkpoints, no error handling. The skill claims to provide 'step-by-step guidance' but contains none. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of generic placeholder text with no references to supporting files, no structured navigation, and no bundle files to support it. There is no meaningful content to organize. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
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- Reviewed
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