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Installable agentic skills / AI agent skills (SKILL.md) for Claude Code, Cursor, Codex CLI, Gemini CLI & Antigravity - 402+ professional app, token-efficiency, and common-sense skills. SEO/GEO ready.

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--- name: iterate-step-by-step description: "Develop a complex deliverable in reviewable stages, carrying forward agreed requirements and decisions." category: common-sense risk: safe source: self source_type: self date_added: "2026-08-26" tags: ["iteration", "scaffolding", "workflow", "multi-turn", "agile", "prompt-engineering"] tools: ["claude", "cursor", "gemini", "codex", "chatgpt"] --- # Iterate Step-by-Step (Conversational Scaffolding) (AI Skill) ## Overview Expecting an AI to produce a finished, 10/10 masterpiece in a single massive prompt (*"Write a complete multi-chapter marketing strategy and all ad copy"*) is a recipe for disappointment. The model spreads its attention across too many variables, producing shallow text and skipped details. The **Conversational Scaffolding Protocol** breaks production into a **4-Turn Agile Loop**: scaffold the outline $\rightarrow$ build the core engine $\rightarrow$ harden edge cases $\rightarrow$ polish the final output. --- ## The 4-Turn Scaffolding Pipeline ``` ┌─────────────────────────────────────────────────────────────┐ 4-Turn Scaffolding Pipeline [ TURN 1: Wireframe / Skeleton ] ──► Agree on structure [ TURN 2: Core Drafting / Build ] ──► Generate meat [ TURN 3: Stress-Test & Edges ] ──► Catch flaws & bugs [ TURN 4: Surgical Polish ] ──► Voice, SEO, & CTA └─────────────────────────────────────────────────────────────┘ ``` --- ## Master Iteration Prompt Templates ### Pattern 1: The 4-Turn Execution Script Use when building a complex deliverable (e.g. business plan, landing page, software module): ```markdown <!-- TURN 1: The Skeleton --> "We are going to build [PROJECT]. Do NOT write the content yet. Give me a 5-point structural outline. I will review and adjust." <!-- TURN 2: The Core Build (After adjusting Turn 1) --> "The outline is locked. Now write Section 1 and Section 2 ONLY. Follow our agreed constraints and focus on high depth." <!-- TURN 3: Edge-Case Hardening --> "Now review what we have so far. Where are the weak points or missing scenarios? Suggest 3 specific additions." <!-- TURN 4: The Final Polish --> "Apply the additions from Turn 3 and output the polished, production-ready version." ``` --- ## Real-World Case Study ### Scenario: Building a High-Converting SaaS Landing Page #### The 1-Shot Megaprompt Failure > **User**: *"Write a complete landing page for my new AI bookkeeping software including headlines, features, pricing, testimonials, and FAQs."* > > *Result: A generic 600-word block of clichéd marketing text ("Revolutionize your finances today! Save time and money!") with zero competitive edge.* #### The 4-Turn Scaffolding Success > - **Turn 1 (Scaffold)**: User asks for a 5-section narrative wireframe $\rightarrow$ AI suggests: Hero $\rightarrow$ Relatable Pain $\rightarrow$ Interactive Demo $\rightarrow$ Social Proof $\rightarrow$ FAQ. User approves. > - **Turn 2 (Hero & Hook)**: User prompts: *"Write 3 bold variations for the Hero Section. Focus on eliminating tax season dread."* User selects the best hook. > - **Turn 3 (Feature Breakdown)**: User prompts: *"Now write the 3 feature blocks highlighting our automated receipt OCR and zero-reconciliation features."* > - **Turn 4 (FAQ & Polish)**: User prompts: *"Generate 4 objection-crushing FAQs addressing data security and accountant collaboration."* **Outcome**: A cohesive, deeply tailored, high-converting landing page built in under 4 minutes with zero token waste. --- ## Why Iteration Beats Megaprompting - 🎯 **Total Creative Steering**: You catch structural flaws in Turn 1 before writing 2,000 words in the wrong direction. - 💡 **Deeper Attention**: The AI devotes 100% of its context window and compute to one section at a time. - **Zero Overwhelm**: You review bite-sized chunks rather than a 10-page wall of text.