train-test-splitter
Train Test Splitter - Auto-activating skill for ML Training. Triggers on: train test splitter, train test splitter Part of the ML Training skill category.
Overall
score
23%
Does it follow best practices?
Validation for skill structure
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill train-test-splitterActivation
7%This description is severely underdeveloped, essentially just restating the skill name without explaining capabilities or providing meaningful usage guidance. It lacks concrete actions, natural trigger terms, and explicit 'when to use' instructions. The only slight positive is that 'train test splitter' is a recognizable ML concept, providing minimal distinctiveness.
Suggestions
Add specific actions the skill performs, e.g., 'Splits datasets into training and test sets, supports stratified splitting, configurable ratios, and random seed control'
Include a 'Use when...' clause with natural trigger terms like 'split data for training', 'create test set', 'holdout validation', 'train_test_split', 'partition dataset'
Remove the duplicate trigger term and expand with variations users would naturally say when needing this functionality
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the skill ('Train Test Splitter') without describing any concrete actions. It doesn't explain what the skill actually does - no mention of splitting data, ratios, stratification, or any specific capabilities. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and the 'when' guidance is essentially just repeating the skill name. There's no explicit 'Use when...' clause with meaningful trigger scenarios. | 1 / 3 |
Trigger Term Quality | The trigger terms listed are redundant ('train test splitter, train test splitter' - duplicated) and miss natural variations users would say like 'split data', 'training set', 'test set', 'holdout', 'validation split', or 'sklearn train_test_split'. | 1 / 3 |
Distinctiveness Conflict Risk | The term 'train test splitter' is fairly specific to ML data splitting, which provides some distinctiveness. However, 'ML Training skill category' is vague and could overlap with other ML-related skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
7%This skill is essentially a placeholder template with no actual instructional content. It describes what a train-test splitter skill would do but provides zero actionable guidance, code examples, or specific techniques. Claude already knows what train-test splitting is and how to implement it - this skill adds no value.
Suggestions
Add executable code examples showing sklearn's train_test_split, stratified splitting, and time-series splitting patterns
Include specific guidance on choosing split ratios, handling imbalanced datasets, and setting random seeds for reproducibility
Remove the generic 'Capabilities' and 'Example Triggers' sections - they waste tokens explaining skill activation rather than teaching the actual skill
Add concrete validation steps like checking class distribution after splitting or verifying no data leakage between sets
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that explains nothing Claude doesn't already know. Phrases like 'provides automated assistance' and 'follows industry best practices' are meaningless filler with no actual information about train-test splitting. | 1 / 3 |
Actionability | No concrete code, commands, or specific guidance is provided. The skill describes what it claims to do but never actually shows how to split data, what functions to use, or any executable examples. | 1 / 3 |
Workflow Clarity | No workflow is defined. There are no steps, no sequence, and no validation checkpoints. The content only describes trigger phrases and vague capabilities without any actual process. | 1 / 3 |
Progressive Disclosure | The content has some structure with clear section headers, but there are no references to detailed materials, no links to examples or API documentation, and the sections themselves contain no substantive content to organize. | 2 / 3 |
Total | 5 / 12 Passed |
Validation
69%Validation — 11 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') | Warning |
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
body_steps | No step-by-step structure detected (no ordered list); consider adding a simple workflow | Warning |
Total | 11 / 16 Passed | |
Reviewed
Table of Contents
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