social-media-analyzer

Found your social-media-analyzer skill while reviewing some recent submissions, and I'm curious about the design choice to separate parsing from analysis—that's usually where folks either go too minimal or over-engineer. The 62/100 puts it in that interesting territory where the core idea is solid but there's a clear gap between concept and execution.

Links:

• GitHub
• Your agentic skill in the SkillzWave marketplace

TL;DR

You're at 62/100, solidly in D territory. Based on Anthropic's best practices for skill architecture. Strongest area is Spec Compliance (11/15)—your frontmatter is clean and properly structured. Weakest is Writing Style (5/10) and Progressive Disclosure Architecture (18/30)—the skill reads more like marketing copy than actionable instructions, and there's a lot of token-inefficient fluff that should be trimmed or moved to supporting files.

What's Working Well

• Solid frontmatter structure - Your YAML is valid and includes all required fields, which puts you ahead on the spec compliance front
• Real supporting files - Having calculate_metrics.py, analyze_performance.py, and reference files shows you thought about modularity
• Specific problem domain - Social media analytics is concrete enough that the skill has real utility potential

The Big One: Missing Trigger Phrases

Here's what's costing you the most points: your description doesn't include trigger phrases. Claude won't know when to use this skill because you haven't told it.

Current description:

Analyzes social media campaign performance across platforms with engagement metrics, ROI calculations...

It needs to be:

Performs social media analysis and campaign performance tracking. Use when asked to 'analyze social media', '...