Content
78%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured, actionable skill that effectively balances conciseness with completeness. It provides clear principles, audience calibration, anti-patterns, and a quality checklist while appropriately deferring detailed examples and data to reference files. The main weakness is the absence of at least one full example email in the body to demonstrate the principles in action, though this may exist in the referenced frameworks.md.
Suggestions
Add one complete example email (with annotations) in the main body to demonstrate the principles working together, rather than deferring all examples to reference files.
Add an explicit revision loop after the Quality Check section: 'If any answer is no, revise and re-check before presenting.'
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient and avoids explaining basic concepts Claude already knows. There's some minor verbosity in sections like 'When to Use' and 'What it should NOT sound like' that could be tightened, but overall it respects Claude's intelligence and keeps guidance practical. | 4 / 5 |
Actionability | The skill provides concrete frameworks, specific anti-patterns, voice calibration by audience type, and a quality checklist. However, it lacks actual example emails showing the principles in action — the frameworks are described in prose rather than demonstrated with full copy-paste examples (those are deferred to reference files). | 4 / 5 |
Workflow Clarity | The workflow is clear: check for context file → gather inputs → write using principles → quality check. The 'Before Writing' section sequences the discovery process well, and the quality check provides validation. Minor gap: no explicit feedback loop for revision if the quality check fails. | 4 / 5 |
Progressive Disclosure | Excellent structure with a clear overview in the main file and well-signaled one-level-deep references to personalization.md, frameworks.md, subject-lines.md, follow-up-sequences.md, and benchmarks.md. Each reference is contextualized with what it contains, and the Data & Benchmarks section provides a clean navigation index. | 5 / 5 |
Total | 17 / 20 Passed |