content-trend-researcher_skill

This skill analyzes trends across multiple platforms to generate data-driven article outlines aligned with user intent.

Python

388

GitHub Stars

8

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill alirezarezvani/claude-code-skill-factory --skill content-trend-researcher

expected_output.json15.3 KB
HOW_TO_USE.md9.0 KB
intent_analyzer.py15.8 KB
outline_generator.py30.2 KB
platform_insights.py30.2 KB
sample_input.json606 B
SKILL.md8.0 KB
trend_analyzer.py17.9 KB

Overview

This skill is an advanced content and topic research assistant that analyzes trends across Google Trends, Google Analytics, Substack, Medium, Reddit, LinkedIn, X, blogs, podcasts, and YouTube to produce data-driven article outlines. It helps creators and marketers identify trending topics, match user intent, and discover content gaps so you can publish higher-performing content. Outputs are practical: platform-specific insights, SEO titles, structured outlines, and promotion recommendations.

How this skill works

The skill aggregates public trend signals and engagement metrics from multiple platforms, classifies user intent, and scores topic opportunity using search volume, engagement, and competition indicators. It generates SEO-optimized titles, H2/H3 outline structures, suggested word counts, internal linking opportunities, and multimedia recommendations based on top-performing content and intent analysis. Results are returned as a structured research report ready for editorial use.

When to use it

Before drafting any long-form content to validate and scope topic selection
When building an editorial calendar or planning pillar + cluster strategies
To find content gaps and angles your competitors miss
To optimize existing content by aligning with current user intent and platform signals
When preparing platform-specific content plans (video, newsletter, blog)

Best practices

Be specific with your topic and audience to improve signal relevance
Select platforms where your target audience actually consumes content
Prioritize primary user intent (informational, commercial, transactional) before outline generation
Use opportunity score and gap analysis to pick low-competition, high-demand angles
Iterate research monthly for fast-changing niches and re-optimize published pieces

Example use cases

Create a 1,800–2,500 word blog outline for "AI automation for small businesses" with intent: informational
Generate platform-specific content ideas and one long-form blog outline for a consumer trend like "sustainable fashion"
Analyze top-performing newsletter and blog posts to produce an outline that fills identified gaps for "email marketing strategies 2025"
Produce 3 article outlines and promotion schedules for "remote work productivity tools" across all platforms

FAQ

Provide topic, platforms, intent_focus, target_audience, content_type, analysis_depth, and desired number_of_outlines in the JSON input format.

Does it use live private data?

No. It uses public trend signals and available engagement metrics; real-time private analytics require API access and credentials which are not bundled.