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Found 30 Skills
Principle-engineering posture for production-grade code: reads the repo first, plans before code, matches conventions, pulls latest docs over training recall, and ships the simplest correct change that holds the bar — proper algorithms and data structures, idempotent writes, schema+queries+indexes as one artefact, typed errors, tests in the same diff. Substrate-agnostic; defers to peer skills on their lanes. Use for non-trivial planning, design, implementation, review, or refactoring; RCA and debugging; performance and optimization work; changes touching a database schema, security, infrastructure, or a public API; hardening inherited, vibe-coded, or LLM-generated code (dependency/CVE and migration audits); and over-engineering cleanup ("simplest solution," "YAGNI," "what can we delete").
Read and summarize an existing codebase before any design or implementation work begins. Use as a prerequisite when the project is not greenfield.
Applies software engineering best practices, design principles, and avoids common anti-patterns. Use when designing systems, reviewing code quality, refactoring legacy code, making architectural decisions, or improving maintainability.
Lead Software Engineer. Use this skill whenever the user mentions coding, debugging, refactoring, or implementation, even if they don't explicitly ask for an "engineer." Use it to translate technical blueprints into clean code.
AI-native software engineering harness. plugkit owns all state and serves every instruction via the spool. The agent dispatches verbs; plugkit tracks phase, mutables, PRD, and recall.
Produce a high-level technical design with architecture diagram, component responsibilities, data flow, and test scenario map. Use after the product intent specification is approved.