audience-research
Use when the user wants to evaluate a creator, influencer, or brand audience using public profile signals, TikTok audience demographics, follower/following…
Skill by ScrapeCreators
Install
Works with Claude Code. Read the repository before you give any tool access to your data.
npx agentmarket install skill/scrapecreators-audience-research
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: design, data, writing, research
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/audience-research
Tools it pre-approves 4
From allowed-tools in SKILL.md: the agent may use these without asking you each time.
Bash,Read,Write,WebFetch
What's inside
- Skill name
audience-research- Description
- Use when the user wants to evaluate a creator, influencer, or brand audience using public profile signals, TikTok audience demographics, follower/following data, comments, geography, language, and content fit. Helps judge sponsorship and market fit.
- License
- MIT
- Allowed tools
- Bash,, Read,, Write,, WebFetch
- Instructions
- 65 lines in SKILL.md · view on GitHub
Before installing
- Pre-approves some shell commands
Files (1)
- SKILL.md
SKILL.md (first lines)
# Audience Research
## Overview
Evaluate whether a creator or social account reaches the right audience. This skill combines available public profile metrics, TikTok audience demographics, regional signals, follower/following data when available, comments, language, and content topics.
## When to Use
Use this skill when the user asks to:
- check if a creator's audience fits a market
- compare audience fit across creators
- find US-heavy, country-specific, or niche-specific creators
- evaluate sponsorship/influencer opportunities
- understand who appears to engage with an account
## Useful Sources
- `/v1/tiktok/user/audience`
- `/v1/tiktok/profile/region`
- profile endpoints across platforms
- follower/following endpoints where available
- comments on recent posts
- link-in-bio pages and creator shops for niche signals
## Workflow
1. Pull profile and available audience/demographic data.
2. Pull recent content and comments if audience intent matters.
3. Extract region, language, niche, product/category, and community signals.
4. Score audience fit against the user's target market.
5. Label confidence based on the strength of public data.
## Output Format
```markdown
# Audience Research: {creator}
## Fit Summary
- Target market:
- Fit score: High/Medium/Low
- Confidence: High/Medium/Low
## Evidence
| Signal | Evidence | Source |
|---|---|---|
## Audience Notes
- Geography:
- Language:
- Niche/content fit:
- Comment quality:
## Sponsorship Recommendation
- Good fit / Maybe / Poor fit
- Why:
```
## Common Pitfalls
- Do not infer exact demographics from vibes. Use available evidence and label assumptions.
- Do not overpromise audience details for platforms that do not expose them publicly.
- Do not ignore mismatch between creator location and audience location.From ScrapeCreators/social-media-research-skills, MIT.
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Signals
- Stars
- 4,674
- Forks
- 92
- Open issues
- 4
- Last commit (this folder)
- Jun 6, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Website
- scrapecreators.com
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
audience-research skill. Agent Mart. https://agentmart.dev/skills/scrapecreators-audience-research (last updated 2026-10-24)