# Social listening brief Human Guide

## What This Is For
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. It gives the agent a clearer input/output frame for social content: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the Social listening brief agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for social listening brief.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the Social listening brief guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- 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
- Reddit search, subreddit search, posts, comments
- TikTok search top/keyword/hashtag and comments
- YouTube search, transcripts, comments
- Instagram reels search and hashtag search
- Google search when platform search is not enough
- Define topic, aliases, competitor names, and date window.
- Search multiple relevant sources, not every source blindly.

## Decision Points And Nuance
The original skill emphasizes: Overview, When to Use, Useful Sources, Workflow, Output Format, Executive Summary, Top Themes, Notable Posts, Risks / Opportunities, Recommended Actions.

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- 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.

## Copy-And-Paste Prompt
```text
Use the Social listening brief human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the scrapecreators/social-media-research-skills skill entry for `social-listening-brief`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# 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

1. Define topic, aliases, competitor names, and date window.
2. Search multiple relevant sources, not every source blindly.
3. Keep URLs, dates, platform, engagement metrics, and exact quotes.
4. Cluster conversations into themes.
5. Separate positive, negative, neutral, and mixed signals.
6. 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.