Social Listening Report

Social listening brief

by ScrapeCreators · MIT license · ★ 2,619 on GitHub · v1.0.0 · updated Aug 26

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…

---
name: social-listening-brief
description: 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.
allowed-tools: Bash, Read, Write, WebFetch

version: 1.0.0
author: ScrapeCreators
license: MIT
homepage: https://scrapecreators.com
repository: https://github.com/ScrapeCreators/social-media-research-skills
metadata:
  openclaw:
    requires:
      env:
        - SCRAPECREATORS_API_KEY
    primaryEnv: SCRAPECREATORS_API_KEY
    homepage: https://scrapecreators.com
    tags:

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.

Manual install (npx, ZIP)

Claude Codenpx skills add ScrapeCreators/social-media-research-skills --skill social-listening-brief -g -a claude-code

Claude Code (degit)

npx degit ScrapeCreators/social-media-research-skills/skills/social-listening-brief#main ~/.claude/skills/social-listening-brief

Claude.ai / desktopZip the folder and upload it under Settings → Capabilities → Skills.

Codex, Cursor, other agentsPoint them at SKILL.md. The other files are plain text.

Connects with Agent Alley MCP · agentalley.io/mcp

Files included

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Outline

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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

# 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.

1	---
2	name: social-listening-brief
3	description: 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.
4	allowed-tools: Bash, Read, Write, WebFetch
5
6	version: 1.0.0
7	author: ScrapeCreators
8	license: MIT
9	homepage: https://scrapecreators.com
10	repository: https://github.com/ScrapeCreators/social-media-research-skills
11	metadata:
12	openclaw:
13	requires:
14	env:
15	- SCRAPECREATORS_API_KEY
16	primaryEnv: SCRAPECREATORS_API_KEY
17	homepage: https://scrapecreators.com
18	tags:
19	- social-media
20	- research
21	- scrapecreators
22	---
23
24	# Social Listening Brief
25
26	## Overview
27
28	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.
29
30	## When to Use
31
32	Use this skill when the user asks:
33
34	- what are people saying about X?
35	- monitor this brand/topic/category
36	- find complaints or praise about a product
37	- summarize recent social discussion
38	- compare sentiment across Reddit, TikTok, YouTube, LinkedIn, Instagram, or Threads
39
40	## Useful Sources
41
42	- Reddit search, subreddit search, posts, comments
43	- TikTok search top/keyword/hashtag and comments
44	- YouTube search, transcripts, comments
45	- Instagram reels search and hashtag search
46	- LinkedIn post search
47	- Threads search
48	- Google search when platform search is not enough
49
50	## Workflow
51
52	1. Define topic, aliases, competitor names, and date window.
53	2. Search multiple relevant sources, not every source blindly.
54	3. Keep URLs, dates, platform, engagement metrics, and exact quotes.
55	4. Cluster conversations into themes.
56	5. Separate positive, negative, neutral, and mixed signals.
57	6. Highlight representative examples and action items.
58
59	## Output Format
60
61	```markdown
62	# Social Listening Brief: {topic}
63
64	## Executive Summary
65	- Main takeaway:
66	- Conversation volume: Low/Medium/High
67	- Sentiment: Positive/Neutral/Negative/Mixed
68	- Confidence: High/Medium/Low
69
70	## Top Themes
71	\| Theme \| Sentiment \| Evidence \| Representative quote/source \|
72	\|---\|---\|---\|---\|
73
74	## Notable Posts
75	- [source](url) — why it matters
76
77	## Risks / Opportunities
78	- ...
79
80	## Recommended Actions
81	1. ...
82	```
83
84	## Common Pitfalls
85
86	- Do not pretend this is exhaustive social monitoring. It is public-data research.
87	- Do not average sentiment across very different communities without caveats.
88	- Do not use engagement as a proxy for truth.