Content
20%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is a verbose conceptual overview with no executable guidance and no links to the actual bundled script or template, leaving Claude without concrete instructions despite the bundle containing the tools to do the work.
Suggestions
Replace the conceptual Overview/How It Works prose with a concrete quick-start example that invokes the bundled analyze_sentiment.py with real arguments and shows expected output.
Cut generic filler (Best Practices platitudes, Integration, Resources placeholders) that restates concepts Claude already knows.
Add clearly signaled references to the bundle, e.g., 'Report template: See assets/sentiment_analysis_report_template.md', and include a validate/review checkpoint for the analysis result.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body restates what sentiment analysis is ('Sentiment Analysis: The skill processes the text using a pre-trained sentiment analysis model') and pads sections like Overview, Best Practices, Integration, and Resources with content Claude already knows, wasting the token budget. | 1 / 3 |
Actionability | There is no executable code, command, named library/model, or copy-paste guidance; the bundled analyze_sentiment.py script is never referenced, and steps merely describe ('The skill processes the text') rather than instruct. | 1 / 3 |
Workflow Clarity | 'How It Works' lists a 3-step sequence (Text Input, Sentiment Analysis, Result Output), but the steps are abstract with no validation checkpoints, no concrete commands, and no feedback loop for the analysis output. | 2 / 3 |
Progressive Disclosure | Sections provide some structure, but the real bundle files (analyze_sentiment.py, sentiment_analysis_report_template.md) are never signaled from the body, and 'Resources' merely lists placeholders ('Project documentation', 'Related skills and commands') rather than clear one-level-deep references. | 2 / 3 |
Total | 6 / 12 Passed |