Content
27%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill attempts to cover three large topics (prompt engineering, agent prompting, persuasion principles) in a single monolithic file, resulting in excessive verbosity and poor organization. It explains many concepts Claude already knows (context windows, few-shot learning, persuasion psychology) and reads more like an educational document than an actionable skill reference. The strongest sections are the concrete good/bad examples in the persuasion principles, but overall the skill would benefit dramatically from aggressive trimming and splitting into focused sub-files.
Suggestions
Split into 3-4 separate files (e.g., PROMPT_PATTERNS.md, AGENT_PROMPTING.md, PERSUASION.md) with SKILL.md serving as a concise overview with links to each
Remove explanations of concepts Claude already knows: what context windows are, what few-shot learning is, what chain-of-thought prompting is, basic persuasion psychology definitions
Add a concrete workflow with validation steps for prompt development: draft → test on edge cases → measure metrics → iterate, with specific checkpoints
Reduce the persuasion principles section to just the table, examples, and quick reference - cut the psychology explanations and research citations
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | This skill is extremely verbose at ~400+ lines. It explains concepts Claude already knows well (what a context window is, what few-shot learning is, what chain-of-thought prompting is, basic persuasion psychology). The entire 'Context Window' section explains what a context window is to an LLM. The persuasion principles section includes extensive psychological explanations that don't add actionable value. Much of this content restates common knowledge. | 1 / 3 |
Actionability | The skill provides some concrete examples (Python templates, prompt structures, markdown examples) but much of the content is descriptive rather than instructive. Sections like 'Best Practices' and 'Common Pitfalls' are generic lists without executable guidance. The persuasion principles provide good/bad example comparisons which are actionable, but the prompt engineering section is more educational than operational. | 2 / 3 |
Workflow Clarity | The 'Progressive Disclosure' pattern shows a clear 4-level sequence, and the 'Prompt Optimization' section shows an iterative versioning approach. However, there are no explicit validation checkpoints or feedback loops for the prompt engineering workflow itself. The 'degrees of freedom' section provides useful categorization but lacks a clear decision workflow. No verification steps for when prompts are deployed to production. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of text combining three distinct topics (prompt engineering patterns, agent prompting best practices, persuasion principles) all in a single file with no references to supporting files. The content would benefit enormously from being split into separate files with a concise overview in SKILL.md pointing to detailed references. No bundle files are provided despite the content length warranting them. | 1 / 3 |
Total | 6 / 12 Passed |