How to Make Claude Code Skills Activate Reliably (scottspence.com)

Developer ran 200+ controlled tests to make Claude Code “skills” trigger reliably and found the common “simple instruction” hook (tell the model to use a skill when keywords match) is essentially a coin flip: ~20% success. They created a testing framework (SQLite logging, multiple hook configs, synthetic + real Claude tests) and four SvelteKit-focused skills, then compared three hooks with Claude Haiku 4.5: simple instruction (20% overall), an LLM-eval pre-check using the API (80%), and a forced-eval client-side hook that requires the model to explicitly evaluate each skill (YES/NO with reasons), call Skill() immediately, then implement (84%). Results: forced-eval was the most consistent (84% overall, perfect on 3/5 prompt types) and requires no extra API, while LLM-eval is cheaper/faster (~10% cost and 17% latency improvement) but can fail spectacularly on complex multi-skill prompts (0% on Form/Route tests). Technical takeaway: the difference is commitment—making the model explicitly “show its work” and activate a skill enforces follow-through and dramatically improves tool usage. Trade-offs include verbosity and extra tokens for forced-eval vs external API dependency and occasional misses for LLM-eval. The author published the svelte-claude-skills repo and claude-skills-cli with both hooks and test harnesses so teams can reproduce, tune prompt commitment mechanisms, and build more reliable tool-using agents.