model-explainability-tool
Model Explainability Tool - Auto-activating skill for ML Training. Triggers on: model explainability tool, model explainability tool Part of the ML Training skill category.
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill model-explainability-toolOverall
score
19%
Does it follow best practices?
Validation for skill structure
Activation
7%This description is severely underdeveloped - it's essentially just a title with metadata rather than a functional skill description. It provides no concrete actions, has duplicate/redundant trigger terms, and lacks any 'Use when...' guidance. Claude would struggle to know when to select this skill or what capabilities it provides.
Suggestions
Add specific concrete actions the skill performs, e.g., 'Generates SHAP values, visualizes feature importance, creates partial dependence plots, explains individual predictions'
Add a 'Use when...' clause with natural trigger terms like 'Use when the user asks to explain model predictions, understand feature importance, interpret ML model behavior, or debug model decisions'
Include natural user phrases as triggers: 'explain why the model predicted', 'feature importance', 'model interpretation', 'SHAP', 'LIME', 'black box explanation'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the tool ('Model Explainability Tool') without describing any concrete actions. There are no verbs indicating what the skill actually does - no mention of specific capabilities like 'generates explanations', 'visualizes feature importance', or 'analyzes model predictions'. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond naming itself, and the 'when' guidance is just a duplicate of the skill name. There is no explicit 'Use when...' clause or meaningful trigger guidance. | 1 / 3 |
Trigger Term Quality | The trigger terms are just the skill name repeated twice ('model explainability tool, model explainability tool'). Missing natural user phrases like 'explain model', 'feature importance', 'SHAP values', 'interpret predictions', 'why did the model predict', etc. | 1 / 3 |
Distinctiveness Conflict Risk | The term 'Model Explainability' is somewhat specific to a niche domain (ML interpretability), which provides some distinctiveness. However, without concrete actions described, it could still overlap with general ML or data science skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%This skill content is essentially a placeholder template with no actual substance. It contains zero actionable information about model explainability - no mention of specific tools (SHAP, LIME, Captum, etc.), no code examples, no workflows for generating explanations, and no guidance on interpreting results. The content would be completely useless for helping anyone with model explainability tasks.
Suggestions
Add concrete code examples for at least one explainability library (e.g., SHAP feature importance, LIME local explanations) with executable Python code
Include a workflow for generating and validating model explanations: train model -> generate explanations -> validate consistency -> visualize results
Remove all generic boilerplate ('provides automated assistance', 'follows best practices') and replace with specific techniques: feature importance, partial dependence plots, attention visualization, etc.
Add references to detailed guides for different explainability approaches (global vs local, model-agnostic vs model-specific) with clear navigation
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that provides no actual information about model explainability tools. Phrases like 'provides automated assistance' and 'follows industry best practices' are meaningless filler that Claude doesn't need. | 1 / 3 |
Actionability | There is zero concrete guidance - no code, no commands, no specific techniques, no tool names (SHAP, LIME, etc.), no examples. The content describes what the skill supposedly does rather than instructing how to do anything. | 1 / 3 |
Workflow Clarity | No workflow is provided whatsoever. Claims to provide 'step-by-step guidance' but contains no actual steps. There are no processes, sequences, or validation checkpoints for any explainability task. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of vague marketing-style text with no structure pointing to detailed materials, no references to implementation guides, and no organization of explainability concepts or techniques. | 1 / 3 |
Total | 4 / 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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