data-export-excel

I took a look at your data-export-excel skill and wanted to share some thoughts.

Links:

• GitHub
• Your agentic skill in the SkillzWave marketplace

The TL;DR

You're at 66/100, which puts you in D territory—needs work, but definitely salvageable. The skill is grounded in real utility (your bioinformatics examples are solid), but the structure and presentation could use some tightening. Your strongest area is Utility (15/20), but Progressive Disclosure Architecture is dragging you down at just 14/30. This is based on Anthropic's skill best practices rubric.

What's Working Well

• Strong examples – Your QC metrics, DEG analysis, and marker gene examples actually show real use cases. That's the kind of concrete stuff that makes skills useful.
• Clear workflow – The 5-step numbered process is easy to follow, and the step-by-step breakdown works well for people unfamiliar with openpyxl.
• Good trigger terms – You mention "export", "Excel", "spreadsheet" naturally throughout, which helps discoverability even if they're not formally declared.

The Big One: Monolithic File Structure

Your entire skill is crammed into a single 244-line SKILL.md file. That's the main thing holding you back—you're losing 8+ points here alone.

Why it matters: Longer files are harder to navigate, they tank token efficiency (which matters for skill activation), and they violate the Progressive Disclosure Architecture principle. The idea is that people should be able to understand your skill quickly at a glance, then dive deeper if they need to.

The fix: Split this into a layered structure:

• Keep SKILL.md under 60 lines (just overview, basic usage, and key examples)
• Create references/formatting-guide.md for advanced formatting options
• Create references/troubleshooting.md for error handling and edge cases
• Create references/examples/ with your DEG analysis and marker gene examples
• Add a Table of Contents at the top of SKILL.md to help navigation

This will bump you up significantly on the PDA pillar.

Other Things Worth Fixing

1. Add trigger phrases to the description – Your frontmatter description doesn't explicitly state when Claude should invoke this. Add something like: "Use when asked to 'export to Excel', 'save data to spreadsheet', or 'create Excel file'." That's a quick 2-point gain on spec compliance.

2. Ditch the second-person voice – Lines like "Convert your data" and "you have" should be imperative: "Convert data to pandas DataFrame format." It's a small shift but makes the writing more professional. Also removes some of the marketing-y phrasing ("professional Excel spreadsheets", "Unlike cloud-hosted solutions").

3. Add validation and feedback loops – Right now you just have a print statement. Add actual verification: check that the file was created, validate that it's readable, maybe count the rows written. This adds error-handling patterns that make your skill more robust (+2 points on utility).

Quick Wins (In Order)

1. Restructure into layered files (~8 points) – biggest bang for buck
2. Add trigger phrases to frontmatter (~2 points) – super easy, immediate gain
3. Fix voice consistency (~2 points) – quick copyedit pass
4. Add validation checks (~2 points) – makes the skill actually bulletproof

Getting these done would push you into the low 80s pretty easily.

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