excel-parser

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

Links:

• GitHub
• Your agentic skill in the SkillzWave marketplace

The TL;DR

You're at 67/100, which puts you in D territory — solid foundation, but needs meaningful work before it's production-ready. Your strongest area is Spec Compliance (12/15), meaning the YAML frontmatter and naming conventions are spot-on. The real drag is Progressive Disclosure Architecture (17/30) — your skill is 371 lines with a lot of repeated logic, and that bloat is hurting discoverability and usability.

What's Working Well

• Spec compliance is tight. Your YAML frontmatter is valid, naming follows conventions, and required fields are all there.
• Real problem-solving approach. The Scout Pattern for intelligent Excel routing addresses an actual pain point — knowing whether to use Pandas or HTML parsing based on file complexity is genuinely useful.
• Clear decision boundaries. The complexity rules (row count thresholds, merge detection) give users a concrete way to decide their path without ambiguity.
• Good trigger terms. 'Excel/CSV', 'complexity analysis', 'merged cells' — these will help people find your skill when they need it.

The Big One: Bloat is Killing Your Architecture Score

Your 371-line SKILL.md has the same HTML conversion logic explained twice, and you're repeating workflow steps in a full implementation template at the bottom that's already documented above. This is a Progressive Disclosure fail — you're not layering complexity, you're duplicating it.

Here's the fix: Move your implementation templates to a separate references/smart_excel_router.py file. Keep SKILL.md focused on the why and when — when to use Scout Pattern, how complexity rules work, decision tree. The reference f...