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CREATE_DEEP_RESEARCH_PROMPT — how to use CREATE_DEEP_RESEARCH_PROMPT how to use CREATE_DEEP_RESEARCH_PROMPT, CREATE_DEEP_RESEARCH_PROMPT alternative, CREATE_DEEP_RESEARCH_PROMPT setup guide, what is CREATE_DEEP_RESEARCH_PROMPT, CREATE_DEEP_RESEARCH_PROMPT vs other research tools, CREATE_DEEP_RESEARCH_PROMPT install, effective prompt generation for AI agents, Deep Research tool optimization, context7 integration

v1.0.0
GitHub

About this Skill

Ideal for Research Agents requiring precise and effective prompts for Deep Research tools, such as Cursor, Windsurf, or Claude Code. CREATE_DEEP_RESEARCH_PROMPT is a skill that translates vague user requests into highly specific, effective prompts for Deep Research tools or agents.

Features

Utilizes Context is King principle for clear objectives
Employs Tech Validation using context7 for accurate terms and versions
Supports classification of different research types, such as Market, Bug, and Tech research
Generates highly specific and effective prompts for Deep Research tools
Ensures noise reduction in research results through clear context

# Core Topics

KyteApp KyteApp
[0]
[0]
Updated: 3/6/2026

Quality Score

Top 5%
47
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add KyteApp/growth-agents-and-skills/CREATE_DEEP_RESEARCH_PROMPT

Agent Capability Analysis

The CREATE_DEEP_RESEARCH_PROMPT MCP Server by KyteApp is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use CREATE_DEEP_RESEARCH_PROMPT, CREATE_DEEP_RESEARCH_PROMPT alternative, CREATE_DEEP_RESEARCH_PROMPT setup guide.

Ideal Agent Persona

Ideal for Research Agents requiring precise and effective prompts for Deep Research tools, such as Cursor, Windsurf, or Claude Code.

Core Value

Empowers agents to generate highly specific and effective research prompts, leveraging context7 for tech validation and ensuring clear objectives, which is crucial for tasks like market research, bug analysis, or tech validation using protocols like context7.

Capabilities Granted for CREATE_DEEP_RESEARCH_PROMPT MCP Server

Translating vague user requests into actionable research prompts
Validating technology terms and versions using context7 for accurate research
Classifying research objectives into market, bug, or tech research for targeted analysis

! Prerequisites & Limits

  • Requires clear understanding of research objectives and context
  • May need additional validation for highly specialized or niche research topics
Project
SKILL.md
2.3 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

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SKILL.md
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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.

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