40 Engineered Prompt Templates for Claude, ChatGPT, and Gemini to Generate Expert‑Level Output

Prompt Collection Overview

After testing more than 500 prompt variations on Claude, ChatGPT and Gemini, 40 engineered prompt templates were selected that reliably generate expert‑level output. Each template specifies a role, contextual constraints, required output format, quality criteria and concrete examples, avoiding generic instructions.

Categories

Writing & Content (01‑10): prompts for article authoring, long‑form threads, email drafting, content repurposing, copy conversion, blog outlining, narrative transformation, title generation, case‑study building, style mimicry.

Analysis & Strategy (11‑20): SWOT analysis, decision matrix, root‑cause analysis, market opportunity scanning, meeting strategy, pricing strategy, competitive disassembly, OKR building, risk assessment, retrospective hosting.

Technology & Development (21‑28): architecture consulting, code review, debug diagnosis, API design, database schema design, test‑case generation, documentation authoring, refactor planning.

Productivity & Personal (29‑35): weekly planner, learning accelerator, negotiation preparation, habit design.

Data & Research (33‑37): data interpretation, survey analysis, research synthesis.

Communication (36‑40): difficult‑conversation preparation, feedback giving, presentation outline, apology writing, elevator pitch.

Template Structure

Each prompt follows a consistent structure:

Define a specific role (e.g., senior content strategist, SWOT analyst).

Provide contextual constraints and required inputs.

Specify the output format (e.g., article length, bullet list, table).

Set quality standards such as paragraph length limits, avoidance of filler language, bolding key sentences.

Include concrete examples or sample data to guide the model.

Usage Guidance

Users copy a prompt, replace placeholder variables (e.g., [topic], [length]) with their own values, and run it on any of the three supported models. The engineered prompts are designed to treat the AI as a reliable production system rather than a casual chatbot.

Reference Reading

Relevant articles that informed the prompt design:

别再把上下文当聊天记录 – discusses treating context as structured input.

Claude发布官方报告，承认存在3处质量退化问题 – outlines known quality‑degradation issues.

刚刚Opus 4.7发布，相比4.6核心变化，与Claude Code搭配最佳实践 – core changes and best practices.

很多企业做完 AI PoC，为什么还是上不了生产 – analysis of AI PoC failures.