confusion-matrix-generator
Confusion Matrix Generator - Auto-activating skill for ML Training. Triggers on: confusion matrix generator, confusion matrix generator Part of the ML Training skill category.
31
3%
Does it follow best practices?
Impact
72%
0.96xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/07-ml-training/confusion-matrix-generator/SKILL.mdQuality
Discovery
7%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 template placeholder that repeats the skill name without providing meaningful detail about capabilities, actions, or usage triggers. It lacks concrete actions, natural trigger terms, and explicit 'use when' guidance, making it nearly useless for skill selection among multiple options.
Suggestions
Add specific concrete actions such as 'Generates confusion matrices from classification model predictions, visualizes true/false positive/negative rates, computes precision, recall, and F1 scores from prediction results.'
Add an explicit 'Use when...' clause with natural trigger terms like 'Use when the user asks about confusion matrices, classification evaluation, model accuracy visualization, true positives/negatives, or prediction performance metrics.'
Remove the redundant duplicate trigger term and replace with diverse natural language variations users might actually say, such as 'confusion matrix', 'classification report', 'model evaluation matrix', 'prediction accuracy table'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description names the domain ('ML Training') and mentions 'confusion matrix generator' but does not describe any concrete actions like 'generates confusion matrices from classification results, visualizes prediction accuracy, computes precision/recall metrics.' It merely states the skill name without elaborating on what it actually does. | 1 / 3 |
Completeness | The description barely answers 'what does this do' (generates confusion matrices, implied by name only) and has no meaningful 'when should Claude use it' clause. The 'Triggers on' line just repeats the skill name rather than providing explicit usage guidance. | 1 / 3 |
Trigger Term Quality | The only trigger term is 'confusion matrix generator' repeated twice. It misses natural variations users would say such as 'confusion matrix', 'classification results', 'prediction accuracy', 'true positives', 'false positives', 'model evaluation', or 'classification metrics'. | 1 / 3 |
Distinctiveness Conflict Risk | The term 'confusion matrix' is fairly specific to a particular ML task, which provides some distinctiveness. However, the vague 'ML Training' category and lack of detailed scope could cause overlap with other ML-related skills. | 2 / 3 |
Total | 5 / 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 shell with no actionable content whatsoever. It repeatedly references 'confusion matrix generator' without ever explaining how to generate a confusion matrix, providing code examples (e.g., using sklearn's confusion_matrix), or defining any workflow. It reads as a template placeholder that was never filled in with actual technical guidance.
Suggestions
Add executable code examples showing how to generate a confusion matrix using sklearn (e.g., `from sklearn.metrics import confusion_matrix; cm = confusion_matrix(y_true, y_pred)`) and how to visualize it with seaborn or matplotlib.
Remove all meta-description sections ('When to Use', 'Example Triggers', 'Capabilities') that describe the skill abstractly and replace them with concrete guidance on interpreting confusion matrix values (TP, FP, TN, FN) and deriving metrics like precision, recall, and F1.
Add a clear workflow: 1) Obtain predictions, 2) Compute confusion matrix, 3) Visualize/log results, 4) Validate against expected class distribution.
Include specific examples with sample input/output showing what a confusion matrix looks like for a multi-class classification problem.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is entirely filler and meta-description. It explains what the skill does in abstract terms without providing any actual technical content. Every section restates the same vague idea ('confusion matrix generator') without adding substance. | 1 / 3 |
Actionability | There is zero concrete guidance—no code, no commands, no examples of actual confusion matrix generation. The content only describes what the skill could do rather than instructing how to do it. | 1 / 3 |
Workflow Clarity | No workflow, steps, or process is defined. The skill mentions 'step-by-step guidance' as a capability but never provides any steps. There are no validation checkpoints or sequenced instructions. | 1 / 3 |
Progressive Disclosure | The content is a flat, repetitive document with no meaningful structure. Sections exist but contain no real content differentiation. There are no references to detailed materials or external files. | 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
3076d78
- Reviewed
Table of Contents
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