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AI優先工程

針對團隊流程、審查閘門或程式碼擁有權規則的工程運作模型,適用於大部分實作輸出由AI代理產生的程式碼庫。

AI優先工程 是什麼?

AI優先工程是一種為團隊設計的運作模型,特別適用於大量依賴AI代理產生程式碼的開發環境。此技能強調在規劃階段投入更多心力,而非追求打字速度,並要求團隊提升評估覆蓋率,以取代單純依賴經驗的信心。在架構上,它偏好明確的邊界、穩定的合約、型別明確的介面以及確定性的測試,避免隱含的行為散佈在難以察覺的慣例中。程式碼審查的重點應轉向系統行為的退化、安全性假設、資料完整性、錯誤處理與部署安全,而將風格問題交由自動化工具處理。此外,此技能也定義了優秀AI優先工程師的特質,包括能夠分解模糊工作、定義可衡量的驗收標準、產生高訊號的提示與評估,以及在交付壓力下維持風險控制。測試標準則需提高,涵蓋回歸覆蓋率、明確的邊界案例斷言以及跨介面的整合檢查。此技能支援Claude Code、Cursor、Codex等平台,幫助團隊建立一套完整且可重複的流程,確保AI輔助程式碼生成的品質與可靠性。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/ai-first-engineering

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開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

AI-First Engineering

當團隊透過 AI 輔助程式碼生成進行開發時,請使用此技能來設計流程、審查及架構。

流程轉變

  1. 規劃品質比打字速度更重要。
  2. 評估覆蓋率比經驗法則的信心更重要。
  3. 審查焦點從語法轉向系統行為。

架構需求

偏向採用對 AI 代理程式友善的架構:

  • 明確的邊界
  • 穩定的合約
  • 型別化介面
  • 確定性測試

避免隱藏在慣例中的隱含行為。

AI-First 團隊中的程式碼審查

審查重點:

  • 行為回歸
  • 安全性假設
  • 資料完整性
  • 錯誤處理
  • 上線安全性

盡量減少花費在已由自動化處理的風格問題上的時間。

招募與評估訊號

優秀的 AI-First 工程師:

  • 能明確拆解模糊的工作
  • 定義可衡量的驗收標準
  • 產出高訊號的提示與評估
  • 在交付壓力下執行風險控制

測試標準

提高對生成程式碼的測試門檻:

  • 受影響領域需有必要的回歸覆蓋率
  • 明確的邊界案例斷言
  • 介面邊界的整合檢查

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/ECC

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

api-connector-builder

Build a new API connector or provider by matching the target repo

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