I've been digging through skill implementations lately, and your approach to language design caught my attention—the way you're handling the progression from theory to practical application is pretty solid. Scored 91, which puts you in that sweet spot where the foundation is strong but there's still room to tighten things up.
Links:
The TL;DR
You're at 91/100, solid A territory. This is based on Anthropic's skill best practices. Your Writing Style is flawless (10/10)—dense, declarative, zero marketing fluff. The Progressive Disclosure Architecture (28/30) is where you're really winning with that layered approach. The one gap is Spec Compliance (12/15)—you're leaving some discoverability on the table.
What's Working Well
- Writing is chef's kiss. Zero second-person pronouns, perfect voice/tense consistency, every token earns its place. That's the kind of precision most skills struggle with.
- Reference architecture is clean. The layering—SKILL.md for core patterns, separate files for error-handling and builtins—shows you understand token economy. Files stay appropriately scoped.
- The Lexer → Parser → AST → Interpreter progression actually works. You've got complete, working examples for each component. That's not common. Most skills half-ass the examples.
- Trigger terms are solid. "lexer", "parser", "AST", "interpreter"—these are the exact terms someone searching for this skill would use. Discoverability is locked in.
The Big One: Add More Trigger Phrases to the Description
Your description mentions only 1-2 trigger phrases when it could have 4-5. Right now you're getting found for specific searches, but you're missing compound searches.
Current state: Description is minimal, hitting the lexer/parser/AST basics.
The fix: Expand the description to include triggers like "domain-specific language", "compiler design", "language implementation", "syntax trees". These are real things people search for when they need this skill.
Example approach:
description: >
Build domain-specific languages (DSLs) and language implementations with production patterns
for lexers, parsers, AST design, and interpreters. Covers syntax design, error recovery,
and compiler architecture.
Impact: +1-2 points on Spec Compliance, better discoverability in the marketplace.
Other Things Worth Fixing
-
Add Table of Contents to reference files. Both references/builtins.md and references/error-handling.md are 192-213 lines without a TOC. Add a simple ## Contents section after the header so people can jump to what they need. (+1 point for Navigation Signals)
-
Error handling reference could showcase test patterns. You cover validation in error-handling.md, but missing explicit test patterns for error cases. A couple examples of how to test lexer/parser error recovery would round out the Feedback Loops score.
-
Consider a TLDR at the top of SKILL.md. Right now it dives into Quick Start—a 2-3 line summary of when/why to use this ("Use this when designing a language or building a compiler") would help someone skim faster.
Quick Wins
- Highest impact: Expand description with 3-4 more trigger phrases (5-10 min) → +1-2 points
- Low effort, clean gain: Add TOC to reference files (10 min) → +1 point
- Polish: Brief TLDR at the top of SKILL.md for context (5 min) → improves readability
You're 9 points away from 100. These fixes are straightforward and genuinely improve the skill for users searching the marketplace.
Checkout your skill here: [SkillzWave.ai](https://skillzwave.ai) | [SpillWave](https://spillwave.com) We have an agentic skill installer that install skills in 14+ coding agent platforms. Check out this guide on how to improve your agentic skills.
I've been digging through skill implementations lately, and your approach to language design caught my attention—the way you're handling the progression from theory to practical application is pretty solid. Scored 91, which puts you in that sweet spot where the foundation is strong but there's still room to tighten things up.
Links:
The TL;DR
You're at 91/100, solid A territory. This is based on Anthropic's skill best practices. Your Writing Style is flawless (10/10)—dense, declarative, zero marketing fluff. The Progressive Disclosure Architecture (28/30) is where you're really winning with that layered approach. The one gap is Spec Compliance (12/15)—you're leaving some discoverability on the table.
What's Working Well
The Big One: Add More Trigger Phrases to the Description
Your description mentions only 1-2 trigger phrases when it could have 4-5. Right now you're getting found for specific searches, but you're missing compound searches.
Current state: Description is minimal, hitting the lexer/parser/AST basics.
The fix: Expand the description to include triggers like "domain-specific language", "compiler design", "language implementation", "syntax trees". These are real things people search for when they need this skill.
Example approach:
Impact: +1-2 points on Spec Compliance, better discoverability in the marketplace.
Other Things Worth Fixing
Add Table of Contents to reference files. Both
references/builtins.mdandreferences/error-handling.mdare 192-213 lines without a TOC. Add a simple## Contentssection after the header so people can jump to what they need. (+1 point for Navigation Signals)Error handling reference could showcase test patterns. You cover validation in error-handling.md, but missing explicit test patterns for error cases. A couple examples of how to test lexer/parser error recovery would round out the Feedback Loops score.
Consider a TLDR at the top of SKILL.md. Right now it dives into Quick Start—a 2-3 line summary of when/why to use this ("Use this when designing a language or building a compiler") would help someone skim faster.
Quick Wins
You're 9 points away from 100. These fixes are straightforward and genuinely improve the skill for users searching the marketplace.
Checkout your skill here: [SkillzWave.ai](https://skillzwave.ai) | [SpillWave](https://spillwave.com) We have an agentic skill installer that install skills in 14+ coding agent platforms. Check out this guide on how to improve your agentic skills.