Software quality review and design guidance for any code: naming, cohesion, coupling, duplication, function size, dependency direction, and testability. Use when someone asks to improve, review, refactor, or design code, or asks what good structure looks like here. Routes to the sub-skill matching the kind of work.
Defensive programming for any code: validating inputs at every boundary, checking for null and absent values, supplying safe fallbacks, catching and logging exceptions, and degrading gracefully rather than failing. Use when someone asks to make code robust, resilient, safer, or harder to crash. Routes to the sub-skill…
AI features you ship to users: structured output, tool schemas, prompt injection, evals. Use when "the model returns bad JSON", "it hallucinates", "stop it calling the wrong tool", "add evals", or an LLM feature can trigger refunds, emails or writes. Covers schema-constrained output, idempotent tool calls…