feat: optimize tdd skill (89% → 99%)#2
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Hullo @mfranzon 👋 I ran your skills through `tessl skill review` at work and found some targeted improvements. Here's the full before/after:  | Skill | Before | After | Change | |-------|--------|-------|--------| | tdd | 89%* | 99% | +10% | *Note: The raw "before" score was 15% because the frontmatter used non-standard field names (`skill:` instead of `name:`, `trigger:` instead of `description:`), which blocked the LLM judge entirely. I fixed the field names first to get a meaningful 89% baseline, then optimized from there. <details> <summary>Changes made</summary> **Frontmatter fixes:** - Renamed `skill:` to `name:` (standard field) - Renamed `trigger:` to `description:` (standard field) - Expanded description with concrete actions: "Writes failing tests, implements minimal passing code, runs the full test suite, and suggests refactoring" **Content improvements (conciseness):** - Removed repeated pause/no-pause rules from the Rules section that were already stated inline in the workflow steps - Tightened parenthetical explanations throughout (e.g., removed "this means either..." phrasing) - Simplified conditional phrasing in Phase 1 input type detection - Cut "no pause needed" / "no pause" redundancies from GREEN and REFACTOR sections **All domain expertise preserved** — TDD methodology, Red-Green-Refactor workflow, language-specific configs, and decomposition patterns are untouched. </details> Honest disclosure — I work at @tesslio where we build tooling around skills like these. Not a pitch - just saw room for improvement and wanted to contribute. Want to self-improve your skills? Just point your agent (Claude Code, Codex, etc.) at [this Tessl guide](https://docs.tessl.io/evaluate/optimize-a-skill-using-best-practices) and ask it to optimize your skill. Ping me - [@popey](https://github.com/popey) - if you hit any snags. Thanks in advance 🙏
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Hullo @mfranzon 👋
I ran your skills through
tessl skill reviewat work and found some targeted improvements. Here's the full before/after:*Note: The raw "before" score was 15% because the frontmatter used non-standard field names (
skill:instead ofname:,trigger:instead ofdescription:), which blocked the LLM judge entirely. I fixed the field names first to get a meaningful 89% baseline, then optimized from there.Changes made
Frontmatter fixes:
skill:toname:(standard field)trigger:todescription:(standard field)Content improvements (conciseness):
All domain expertise preserved — TDD methodology, Red-Green-Refactor workflow, language-specific configs, and decomposition patterns are untouched.
Honest disclosure — I work at @tesslio where we build tooling around skills like these. Not a pitch - just saw room for improvement and wanted to contribute.
Want to self-improve your skills? Just point your agent (Claude Code, Codex, etc.) at this Tessl guide and ask it to optimize your skill. Ping me - @popey - if you hit any snags.
Thanks in advance 🙏