How do I install the CREATE_DEEP_RESEARCH_PROMPT skill?

Run npx skillmds add majiayu000/create-deep-research-prompt in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Which AI agents work with CREATE_DEEP_RESEARCH_PROMPT?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is CREATE_DEEP_RESEARCH_PROMPT free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published CREATE_DEEP_RESEARCH_PROMPT?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

CREATE_DEEP_RESEARCH_PROMPT by majiayu000

Name: CREATE_DEEP_RESEARCH_PROMPT
Rating: 4.2 (5 reviews)
Author: majiayu000

CREATE_DEEP_RESEARCH_PROMPT

Generate a structured deep research prompt. USE WHEN the user needs to research a complex topic, market, or bug deeply. Capabilities include objective clarification, tech stack validation, and prompt generation.

majiayu000 056c201 2 files · 3.5 KB Updated Sep 9, 2026 567 repo stars

File contents

CREATE DEEP RESEARCH PROMPT

Owner: Manny (Product Manager)

Goal

To translate a vague user request (e.g., "Research AI frameworks") into a highly specific, effective prompt for a Deep Research tool or agent.

Core Principles

Context is King: A research prompt without clear objectives yields noise.
Tech Validation: If researching technology, use context7 to ensure terms and versions are correct.
Classification: Different research (Market vs. Bug vs. Tech) requires different prompt structures.

Workflow Instructions

1. Classification

Action: Determine the research type.
- Product Validation (Do users actually need this?)
- Technical Review (Is this feasible?)
- Bug Diagnosis (Why is this breaking?)
- Market Analysis (Who are the benchmarks?)

2. Objective Clarification

Action: Elicit the "Why."
Prompt: "What decision will this research enable?" or "What is the single most important question to answer?"
Constraint: Stop if the goal is "just curious." Push for actionable intent.

3. Context & Tech Validation

Action: If the research involves specific tools/libraries:
- Call context7 MCP to verify the library names and current versions.
- Example: If user says "Research Next.js router," verify if they mean Pages or App Router.

4. Constructing the Prompt

Action: Assemble the research directive.
Structure:
- Objective: The "North Star" question.
- Key Questions: 3-5 specific sub-questions.
- Methodology: How to search (e.g., "Compare documentation," "Search forums," "Read whitepapers").
- Sources: Define authorized sources (e.g., "Official docs only," "GitHub issues," "Reddit").
- Deliverable: What the output should look like (Table, Summary, Code snippets).

5. Review & Export

Action: Present the draft prompt to the user.
Refine: Incorporate feedback.
Output: Save the final prompt as a Markdown file in outputs/research_prompts/.

Anti-Patterns

NEVER generate a generic "Tell me about X" prompt.
NEVER include hallucinated library versions in a research prompt.
NEVER skip the "Success Criteria" definition.

Output Format

A Markdown file containing the structured prompt, ready to be fed into a reasoning model or research agent.

---name: create-deep-research-promptdescription: Generate a structured deep research prompt. USE WHEN the user needs to research a complex topic, market, or bug deeply. Capabilities include objective clarification, tech stack validation, and prompt generation.--- # CREATE DEEP RESEARCH PROMPT **Owner:** Manny (Product Manager) ## Goal To translate a vague user request (e.g., "Research AI frameworks") into a highly specific, effective prompt for a Deep Research tool or agent. ## Core Principles - **Context is King:** A research prompt without clear objectives yields noise. - **Tech Validation:** If researching technology, use `context7` to ensure terms and versions are correct. - **Classification:** Different research (Market vs. Bug vs. Tech) requires different prompt structures. ## Workflow Instructions ### 1. Classification - **Action:** Determine the research type. - *Product Validation* (Do users actually need this?) - *Technical Review* (Is this feasible?) - *Bug Diagnosis* (Why is this breaking?) - *Market Analysis* (Who are the benchmarks?) ### 2. Objective Clarification - **Action:** Elicit the "Why." - **Prompt:** "What decision will this research enable?" or "What is the single most important question to answer?" - **Constraint:** Stop if the goal is "just curious." Push for actionable intent. ### 3. Context & Tech Validation - **Action:** If the research involves specific tools/libraries: - Call `context7` MCP to verify the library names and current versions. - *Example:* If user says "Research Next.js router," verify if they mean Pages or App Router. ### 4. Constructing the Prompt - **Action:** Assemble the research directive. - **Structure:** - **Objective:** The "North Star" question. - **Key Questions:** 3-5 specific sub-questions. - **Methodology:** How to search (e.g., "Compare documentation," "Search forums," "Read whitepapers"). - **Sources:** Define authorized sources (e.g., "Official docs only," "GitHub issues," "Reddit"). - **Deliverable:** What the output should look like (Table, Summary, Code snippets). ### 5. Review & Export - **Action:** Present the draft prompt to the user. - **Refine:** Incorporate feedback. - **Output:** Save the final prompt as a Markdown file in `outputs/research_prompts/`. ## Anti-Patterns - **NEVER** generate a generic "Tell me about X" prompt. - **NEVER** include hallucinated library versions in a research prompt. - **NEVER** skip the "Success Criteria" definition. ## Output Format A Markdown file containing the structured prompt, ready to be fed into a reasoning model or research agent.

Frequently asked questions