
finding-youtube-micro-influencers
Finds YouTube micro-influencers and niche creators using apidojo's YouTube scraper on Apify. Triggers when the user asks to: find YouTube channels under 100k subscribers in a niche, discover emerging YouTube creators for sponsorship deals, find YouTubers covering a specific topic, identify high-engagement YouTube channels with smaller audiences, build a YouTube influencer outreach list, compare YouTube channel growth rates in a category, or find YouTube channels for affiliate or brand partnership programs. Returns channel name, subscriber count, total views, average views per video, and contact info. Ideal for brand sponsors, podcast networks, and affiliate marketing teams.
- Installs
- 808
- Last 24h
- +15
- Trending rank
- #7034
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/apidojo-io/apidojo-skills --skill finding-youtube-micro-influencers- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads finding-youtube-micro-influencers automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Finding YouTube Micro-Influencers
Searches YouTube for channels in a specific niche, then filters by subscriber count to surface micro-influencers (typically under 100K subscribers) who have high engagement relative to their audience size. Ideal for affiliate programs and brand sponsorships where micro audiences convert better.
Prerequisites
APIFY_TOKENenvironment variable set- Optional: Apify MCP server installed
Inputs
| Parameter | Type | Required | Default | Notes |
|---|---|---|---|---|
startUrls | array | Optional | [] | YouTube URLs — channels, playlists, Shorts, search results |
youtubeHandles | array | Optional | [] | YouTube channel handles (e.g. @kurzgesagt) |
getTrending | boolean | Optional | false | Retrieve trending videos |
keywords | array | Optional | [] | Search keywords |
gl | string | Optional | us | Country code for results (e.g. US, GB) |
hl | string | Optional | en | Language code (e.g. en, de) |
uploadDate | string | Optional | all | Upload date filter: any, hour, today, week, month, year |
duration | string | Optional | all | Duration filter: any, short, long |
features | string | Optional | all | Feature filter: 4k, hd, live, cc, 3d, hdr, etc. |
sort | string | Optional | r | Sort order for search results |
maxItems | number | Optional | Unlimited | Maximum videos to return |
customMapFunction | string | Optional | — | JavaScript function to transform each output object |
Workflow
Progress:
- [ ] Step 1: Define niche and subscriber range
- [ ] Step 2: Build keyword and search term list
- [ ] Step 3: Run youtube-scraper
- [ ] Step 4: Filter and calculate view-to-sub ratio
- [ ] Step 5: Deliver ranked channel list
Step 1: Clarify Parameters
Ask the user for:
- Niche/topic (e.g., "personal finance for millennials", "vegan cooking", "PC gaming")
- Max subscribers (default: 100,000 — micro-influencer threshold)
- Min subscribers (default: 5,000 — filters out very new channels)
- Min videos (default: 20 — ensures established presence)
- Number of channels to return (default: 30)
Step 2: Build Search Term List
Generate 3-5 YouTube search queries for the niche. Think like a viewer, not a marketer:
- Personal finance →
"how to save money","budget for beginners","investing in your 20s" - Vegan cooking →
"easy vegan recipes","vegan meal prep","vegan on a budget" - PC gaming →
"budget PC build","PC gaming tips","indie game reviews"
Step 3: Run the Actor
Recommended — run_actor.js (handles waiting, output, and file saving automatically):
# Quick answer (prints table to chat)
node scripts/run_actor.js \
--actor "apidojo~youtube-scraper" \
--input '{"param": "value"}'
# Save as CSV
node scripts/run_actor.js \
--actor "apidojo~youtube-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.csv --format csv
# Save as JSON
node scripts/run_actor.js \
--actor "apidojo~youtube-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.json --format json
APIFY_TOKENmust be set in environment or.envfile.
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~youtube-scraper"
Input:
{
"searchQuery": "[SEARCH_TERM]",
"maxResults": 50,
"scrapeVideoDetails": false,
"scrapeChannelDetails": true
}
Run for each search query. Merge channel results, deduplicate by channel ID.
REST API fallback:
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~youtube-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"searchQuery": "[SEARCH_TERM]",
"maxResults": 50,
"scrapeChannelDetails": true
}'
Wait for SUCCEEDED. Fetch dataset.
Step 4: Filter and Score
Apply subscriber range filter. Then calculate view-to-subscriber ratio as the micro-influencer quality signal:
view_ratio = (total_views / subscriber_count)
recent_momentum = avg_views_last_10_videos / subscriber_count
High recent_momentum (>0.5) = channel punching above its weight — ideal micro-influencer.
Step 5: Format Output
Output Format
# YouTube Micro-Influencer Discovery: [NICHE]
Subscriber range: [MIN]–[MAX] | Results: [N] channels | Date: [DATE]
| # | Channel | Subscribers | Avg Views | View/Sub Ratio | Videos | Contact | URL |
|---|---------|-------------|-----------|----------------|--------|---------|-----|
| 1 | [name] | [N] | [N] | [X.Xx] | [N] | [email?]| [url] |
## Top 5 Picks for Outreach
1. **[Channel Name]** — [N] subs | [X.Xx] view ratio | Posts [X]x/month
Why: [brief reason — high engagement, relevant niche, consistent posting]
Contact: [email from About page if available]
Latest video: "[title]" — [N] views
2–5. [same structure]
## Notes
- [N] channels found total across all search queries
- [N] filtered out (outside subscriber range or too few videos)
- View/Sub Ratio > 1.0 = exceptional engagement (views exceed subscriber count per video avg)
Troubleshooting
Only large channels in results: YouTube search ranks by relevance + views, surfacing big channels first. Try more niche-specific search terms or filter more aggressively on subscriber count. No contact info: Most YouTubers list business email in the About tab. If missing from scraper output, check the channel URL manually. Stale subscriber counts: YouTube data on Apify can be 24-72h old. For final outreach list, verify top picks manually.
FAQ
What does the finding-youtube-micro-influencers skill do?
Finds YouTube micro-influencers and niche creators using apidojo's YouTube scraper on Apify. Triggers when the user asks to: find YouTube channels under 100k subscribers in a niche, discover emerging YouTube creators for sponsorship deals, find YouTubers covering a specific topic, identify high-engagement YouTube channels with smaller audiences, build a YouTube influencer outreach list, compare YouTube channel growth rates in a category, or find YouTube channels for affiliate or brand partnership programs. Returns channel name, subscriber count, total views, average views per video, and contact info. Ideal for brand sponsors, podcast networks, and affiliate marketing teams.
How do I install finding-youtube-micro-influencers?
Run npx skills add https://github.com/apidojo-io/apidojo-skills --skill finding-youtube-micro-influencers in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/finding-youtube-micro-influencers/ (personal) or .claude/skills/finding-youtube-micro-influencers/ (project).
Which AI agents can use finding-youtube-micro-influencers?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is finding-youtube-micro-influencers safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains finding-youtube-micro-influencers?
It is published by apidojo-io in apidojo-io/apidojo-skills. It has 808 recorded installs.
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