Content
46%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill reads more like a prompt engineering tutorial for humans than a skill file for Claude. It extensively explains concepts Claude already knows (chain-of-thought, few-shot learning, structured output) and would benefit enormously from assuming Claude's existing competence. The concrete prompt templates are useful but the overall structure is too verbose and monolithic for effective use as a skill.
Suggestions
Remove explanations of concepts Claude already knows (what CoT is, what few-shot means, what hallucination is) and reduce to just the actionable patterns/templates with minimal framing.
Split detailed pattern examples (CoT, few-shot, JSON output, hallucination reduction) into separate reference files and keep SKILL.md as a concise overview with links.
Add an explicit feedback loop: after optimizing a prompt, test it, evaluate the output against criteria, and iterate if needed — this is critical for an 'optimization' skill.
Remove the 'When to Use This Skill' section entirely — Claude can determine applicability from the skill description and content without being told when to use it.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill extensively explains concepts Claude already knows well — prompt engineering techniques like chain-of-thought, few-shot examples, JSON output formatting, and hallucination reduction are core LLM knowledge. The 'When to Use This Skill' section, the RSCIT framework explanation, and much of the best practices are things Claude would already understand. The overview paragraph is padded with unnecessary context. | 2 / 5 |
Actionability | The skill provides concrete, copy-paste-ready prompt templates for each pattern (CoT, few-shot, JSON output, hallucination reduction) with clear before/after examples. However, these are prompt templates rather than executable code, and the guidance is more about general prompt engineering principles than a specific executable workflow. The troubleshooting section provides actionable fixes. | 4 / 5 |
Workflow Clarity | The numbered steps (1-7) provide a reasonable sequence from diagnosis through optimization patterns, and the audit checklist adds a validation checkpoint. However, there's no feedback loop — no step to test the optimized prompt, evaluate results, and iterate. For a skill about optimization, the absence of a validate-and-iterate cycle is a notable gap. | 3 / 5 |
Progressive Disclosure | The content is a monolithic ~180-line file with no references to supporting files. The detailed pattern examples (CoT, few-shot, JSON, hallucination reduction) could each be separate reference files, with the main SKILL.md serving as a concise overview. There are no bundle files, and the content that should be split out is all inlined. | 2 / 5 |
Total | 11 / 20 Passed |