performing-regression-analysis

Execute this skill empowers AI assistant to perform regression analysis and modeling using the regression-analysis-tool plugin. it analyzes datasets, generates appropriate regression models (linear, polynomial, etc.), validates the models, and provides performa... Use when analyzing code or data. Trigger with phrases like 'analyze', 'review', or 'examine'.

Quality

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

35%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The skill body is well-sectioned but generic and largely non-actionable: it describes workflow steps abstractly, includes template filler, and fails to point to the bundled scripts and assets that should drive execution. Adding concrete script invocations and validation feedback loops would substantially raise its quality.

Suggestions

Replace abstract descriptions with concrete, executable guidance — e.g., invoke the bundled scripts (`python scripts/validate_data.py`, `scripts/generate_model.py`, `scripts/evaluate_model.py`) with expected inputs and outputs.

Add explicit validation checkpoints and a fix-and-retry loop (validate data -> fix issues -> re-validate -> generate model -> evaluate) so the workflow has real feedback loops.

Link the bundled resources from the body (e.g., point to `assets/example_dataset.csv` and `assets/model_visualization_template.py`) and remove filler sections like 'Output', 'Resources', and the generic 'Instructions' list.

Dimension	Reasoning	Score
Conciseness	The body does not over-explain regression concepts Claude already knows, but it is padded with template filler such as 'The skill produces structured output relevant to the task', 'Project documentation', and 'Invoke this skill... Apply modifications as needed' that add no value.	2 / 3
Actionability	There is no executable code or concrete commands anywhere; it describes ('Claude analyzes...', 'Claude generates...') rather than instructs, and it ignores the bundled scripts (validate_data.py, generate_model.py, evaluate_model.py) entirely.	1 / 3
Workflow Clarity	A four-step sequence (Data Analysis, Model Generation, Model Validation, Performance Reporting) is present, but there are no explicit validation checkpoints or fix-and-retry feedback loops despite validation being a core step.	2 / 3
Progressive Disclosure	The body is organized into clear sections, but the real bundle files (scripts and assets) are never referenced or linked from SKILL.md, leaving them orphaned rather than clearly signaled for navigation.	2 / 3
	Total	7 / 12 Passed

Description

42%

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 covers the regression domain with a what-and-when structure, but suffers from broken/truncated phrasing, generic trigger terms, and high conflict risk with non-regression skills. Tightening the triggers to regression-specific language and repairing the truncated text would materially improve it.

Suggestions

Repair the truncated text ('provides performa...') and the broken opening 'Execute this skill empowers AI assistant' so the description reads as clean third-person voice.

Replace generic triggers ('analyze', 'review', 'examine', 'code or data') with regression-specific phrases such as 'regression analysis', 'fit a regression model', 'predict continuous outcomes', or 'analyze variable relationships'.

Narrow the 'Use when' clause to regression scenarios (e.g., predicting a continuous target or modeling variable relationships) to reduce conflict with code-review and general data-analysis skills.

Dimension	Reasoning	Score
Specificity	It lists several actions ('analyzes datasets, generates appropriate regression models (linear, polynomial, etc.), validates the models') but the report action is truncated ('provides performa...') and 'analyzes datasets' is generic, so it names the domain and some actions without being comprehensive or clean.	2 / 3
Completeness	It states both what it does and a 'Use when analyzing code or data' trigger clause, but the 'when' is broad and weakly tied to regression scenarios while the 'what' is partly truncated, so it does not clearly answer both at full strength.	2 / 3
Trigger Term Quality	It offers natural terms ('analyze', 'review', 'examine', 'data') a user might say, but these are overly generic and it omits regression-specific variations like 'regression', 'fit a model', or 'predict'.	2 / 3
Distinctiveness Conflict Risk	Triggers like 'review', 'examine', and 'analyzing code or data' are very generic and would fire for code review, document review, and many other skills, creating high conflict risk.	1 / 3
	Total	7 / 12 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
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	14 / 16 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Commit: 2cafb23

Reviewed: 2 days ago

Table of Contents

Discovery Implementation Validation

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