streaming-llm-responses

I checked out your streaming implementation—the way you're handling response lifecycle events across different UI patterns is solid, and your reference file docs are thorough. One thing I'm wondering though: with those client effect handlers, how are you ensuring the UI state stays in sync when network latency causes events to arrive out of order?

Links:

• GitHub
• Your agentic skill in the SkillzWave marketplace

The TL;DR

You're at 88/100, B-grade—solid production-ready territory. This is graded against Anthropic's Claude Skills best practices. Your writing style is crisp (9/10), and the utility is genuinely practical for streaming UIs (18/20). Weakest spot: spec compliance at 12/15, mostly because your trigger descriptions could be more complete.

What's Working Well

• PDA structure is efficient — Your main SKILL.md (338 lines) stays focused, and you're smart about pushing full config details to streaming-patterns.md. That's the right call for token economy.
• Your examples are genuinely useful — Five different patterns covering map updates, form streams, game state, and chat UI aren't just fluff. They're actionable, with input/output pairs that show exactly what to expect.
• Terminology consistency — "Client Effect," "Client Tool," "Response Lifecycle"—you stick with these throughout. Makes the mental model stick.
• Writing is dense and Claude-appropriate — No marketing noise, no unnecessary explanation. You respect the reader's time.

The Big One: Missing Table of Contents

Your main file is 338 lines without a TOC, and the reference file hits 211 lines the same way. For files over 100 lines, this kills navigation. Someone jumping in needs to know sections exist—Quick Start, Response Lifecycle, Core Patterns, Anti-...