social-listening-brief

Original：🇺🇸 English

Translated

Use when the user wants a social listening report about what people are saying about a brand, person, product, topic, category, or niche across public social platforms. Produces cited themes, sentiment caveats, notable posts, and recommended actions.

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Sourcescrapecreators/social-media-research-skills

Added on2026-08-12

NPX Install

npx skill4agent add scrapecreators/social-media-research-skills social-listening-brief

SKILL.md Content

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Social Listening Brief

Overview

Research what people are saying publicly across social platforms. This is useful for brand monitoring, category research, product feedback, reputation checks, and understanding recent conversations.

When to Use

Use this skill when the user asks:

what are people saying about X?
monitor this brand/topic/category
find complaints or praise about a product
summarize recent social discussion
compare sentiment across Reddit, TikTok, YouTube, LinkedIn, Instagram, or Threads

Useful Sources

Reddit search, subreddit search, posts, comments
TikTok search top/keyword/hashtag and comments
YouTube search, transcripts, comments
Instagram reels search and hashtag search
LinkedIn post search
Threads search
Google search when platform search is not enough

Workflow

Define topic, aliases, competitor names, and date window.
Search multiple relevant sources, not every source blindly.
Keep URLs, dates, platform, engagement metrics, and exact quotes.
Cluster conversations into themes.
Separate positive, negative, neutral, and mixed signals.
Highlight representative examples and action items.

Output Format

markdown

# Social Listening Brief: {topic}

## Executive Summary
- Main takeaway:
- Conversation volume: Low/Medium/High
- Sentiment: Positive/Neutral/Negative/Mixed
- Confidence: High/Medium/Low

## Top Themes
| Theme | Sentiment | Evidence | Representative quote/source |
|---|---|---|---|

## Notable Posts
- [source](url) — why it matters

## Risks / Opportunities
- ...

## Recommended Actions
1. ...

Common Pitfalls

Do not pretend this is exhaustive social monitoring. It is public-data research.
Do not average sentiment across very different communities without caveats.
Do not use engagement as a proxy for truth.