answer-engine-optimization

I took a look at your answer-engine-optimization skill and noticed the PDA score is dragging things down—you've got solid foundational concepts, but the guide structure could be way more token-efficient if you break up those massive sections and add progressive disclosure checkpoints. What's your thinking on the current organization?

Links:

• GitHub
• Your agentic skill in the SkillzWave marketplace

The TL;DR

You're at 43/100, which puts you in F territory. This is based on Anthropic's 5-pillar grading framework for agentic skills. Your strongest area is Utility (14/20)—the core problem you're solving is real and the feature set is comprehensive. Your biggest weakness is Spec Compliance (0/15)—there's no frontmatter at all, which is a hard blocker for skill metadata.

What's Working Well

• Real problem-solving power: AEO is a legitimate need, especially as LLMs become more prominent in search. Your approach to E-E-A-T analysis and citation tracking addresses a genuine pain point.
• Extensive configuration flexibility: TARGET_INDUSTRY, GEOGRAPHIC_REGION, and optimization levels give users real degrees of freedom to customize their approach.
• Good command documentation: Your numbered steps and examples for commands are clear and easy to follow—that 4/5 workflow clarity score is earned.

The Big One: Missing Frontmatter

This is your biggest blocker. The skill has zero frontmatter—no YAML at the top with name, description, version, or trigger phrases. This isn't just a documentation thing; it's how the marketplace and Claude actually discover and invoke the skill.

Fix: Add this to the very top of SKILL.md:

---
name: answer-engine-optimization
description: Optimize content for AI citation using E-E-A-T analysis and structure optimization. Use when asked to "aeo-audit", "optimize for answer engines", "LLM citation optimization", or "answer engine optimization".
version: 1.0.0
author: alirezarezvani
---

This alone gets you +5 points on spec compliance.

Other Things Worth Fixing

1. Trim the marketing voice (lines 1-50, scattered throughout): Replace "Transform your content," "game-changing," and testimonials with direct instructional language. Change "Get your content cited" to "Optimize content for citation by AI models." This fixes your 1/4 voice and tone score and reclaims ~80 lines. Impact: +4 points.

2. Move installation/setup to references: Your SKILL.md is 615 lines—way too dense. Installation steps (lines 315-355), troubleshooting, and roadmap should go to separate reference files (INSTALLATION.md, TROUBLESHOOTING.md). SKILL.md should stay under 200 lines. Impact: +6 points on PDA.

3. Add a Table of Contents: With content this long, navigation matters. A simple TOC at the top helps Claude (and humans) jump to relevant sections. Impact: +3 points on navigation signals.

4. Include before/after examples: You have usage examples, but no actual content samples showing what "optimized for AEO" looks like. Add 2-3 examples of original content → optimized content with annotations. Impact: +2 points on utility.

Quick Wins

• Add frontmatter now (+5 points)—literally 4 lines, biggest bang for buck
• Strip marketing copy (+4 points)—search/replace "Transform", "game-changing", remove testimonials
• Delegate to references (+6 points)—move setup, troubleshooting, roadmap to separate files
• Add a TOC (+3 points)—one simple section at the top listing all major sections

You're sitting at 43/100, but these four fixes alone would push you over 60. The utility foundation is there—the execution just needs tightening.

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