wc-research

Generate audience-targeted research plans from seed data using Gemini.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/strivelogic-cto/writing-companion.io --skill wc-research
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: wc-research
Source: https://github.com/strivelogic-cto/writing-companion.io/tree/main/skills/wc-research
Command: npx skills add https://github.com/strivelogic-cto/writing-companion.io --skill wc-research

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables structured, audience-aware research to inform content strategy. It reads seed data, identifies gaps, and designs targeted Gemini-based research queries to produce a coherent research synthesis for writing- or product-related content.

Core Features & Use Cases

  • Build audience-targeted research plans from seed sources and metadata.
  • Run iterative Gemini-based rounds to deepen insights and surface actionable findings.
  • Output research plan and synthesis ready for article or content production.

Quick Start

Run the wc-research skill to develop audience-targeted research queries from seed data.

Frequently Asked Questions about wc-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I plan audience-focused research from seed data for content strategy?

Plan audience-focused research by reading seed data to identify gaps and generating targeted Gemini queries to produce a coherent research synthesis for content strategy. This structured approach ensures your research directly informs writing or product content.

What is audience-aware research synthesis and when do I need it?

Audience-aware research synthesis is the process of using seed sources and metadata to generate targeted queries that surface actionable findings. You need it when deep audience insights are required to guide article or product content production.

How do I generate targeted research queries using Gemini from seed sources?

Generate targeted Gemini research queries by analyzing your seed sources and metadata to identify information gaps, then designing iterative research rounds that deepen insights and produce a structured synthesis ready for content creation.

Can I use seed metadata files to build a structured research plan in JSON and Markdown?

Yes, you can reference seed sources and metadata files to build a structured research plan. The plan is output in JSON format and translated into a Markdown plan file, ensuring outputs follow required formats for subsequent deep research rounds.

What is the best way to structure deep audience research for content production?

The best way to structure deep audience research is to run iterative Gemini-based rounds that deepen insights and surface actionable findings, outputting both a research plan and synthesis ready for article or content production.

Do I need existing audience guides to run deep research rounds with this approach?

Yes, the research plan references available audience guides along with seed sources and metadata to prepare and spawn subsequent deep research rounds, ensuring the generated queries are properly targeted for your specific audience context.