菜单
Reduce complexity while preserving behavior. Use when working code has become hard to read, risky to change, or over-engineered.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | code-simplification |
| description | Reduce complexity while preserving behavior. Use when working code has become hard to read, risky to change, or over-engineered. |
| license | MIT |
| compatibility | Works with coding agents that support Agent Skills. Upstream source is Addy Osmani's agent-skills repository. |
| metadata | {"agentpacks.version":"0.1.0","agentpacks.source":"https://github.com/addyosmani/agent-skills/tree/main/skills/code-simplification","agentpacks.upstream":"addyosmani/agent-skills/code-simplification"} |
This registry entry references the upstream code-simplification Agent Skill. Installers should use agentpacks.source and avoid copying upstream content into this registry.
Create, critique, and operationalize engineering strategy documents using diagnosis, tradeoff exploration, guiding policy, coherent actions, and operating cadence. Use when an engineering leader needs strategy for a team, platform, architecture, migration, reliability program, or multi-quarter technical investment.
Run engineering leadership reviews across strategy, delivery, quality, architecture, launch readiness, security risk, and performance health.
Inspect GitHub pull requests for leadership-relevant release risk, quality gates, ownership, and follow-up actions.
Keep dependencies secure, minimal, and up to date. Use when auditing a project's supply chain, adding new libraries, evaluating upgrades, or hardening a CI pipeline against dependency risks.
Design and implement GraphQL APIs with correct schema design, resolver patterns, N+1 prevention, federation, and security. Use when building or evolving a GraphQL layer.
Make ML experiments reproducible and comparable by tracking hyperparameters, metrics, artifacts, and environments. Use when training models, tuning hyperparameters, or promoting models to production.
