AGENT SKILLBY SUPERAMPED
Influencer discovery
AT A GLANCE
Influencer discovery is a social media skill for AI agents. Use when finding influencers to partner with for sponsorships, affiliate deals, or co-marketing. The superamped/ai-marketing-skills repository on GitHub, maintained by superamped, has 49 stars and the MIT license. To add it, run npx skills add superamped/ai-marketing-skills --skill influencer-discovery
- SOURCE REPOSITORY
- superamped/ai-marketing-skills (opens GitHub in a new tab)
- REPO STARS
- SOURCE REPOSITORY
- LICENSE
- MIT
- CATEGORIES
- SKILL.MD SIZE
- 8.1 KB202 LINES
QUICK ANSWER
- WHAT IT IS01
- Use when finding influencers to partner with for sponsorships, affiliate deals, or co-marketing. What sets it apart is how it narrows influencer discovery into one specific workflow rather than a broad, generic prompt.
- INPUTS02
- Context the agent needs: your goals, audience, constraints, and any source material the skill asks for.
- OUTPUT03
- A ready-to-use result: the analysis, copy, or recommendations the agent produces.
INSTALL
One command adds this skill from its source repository.
npx skills add superamped/ai-marketing-skills --skill influencer-discoveryREAD THE SKILL.MD BELOW BEFORE YOU RUN IT. SKILLS INSTRUCT YOUR AGENT.
SKILL.MD
The full file, as published in the source repository. Copy it, download it or open it on GitHub.
ON THIS PAGE · 14
Influencer Discovery#
Usage#
Use when finding influencers to partner with for sponsorships, affiliate deals, or co-marketing. Also useful for identifying thought leaders your target audience already follows, building a media list for outreach or PR, or understanding who shapes opinion in your niche before creating content.
Process#
Step 1: Gather Inputs#
Ask the user for:
- Industry/niche — the topic domain (e.g., "B2B SaaS marketing", "personal finance for millennials", "indie game development")
- Target audience — who follows these influencers, framed as the buyer (e.g., "SaaS founders", "freelance developers", "e-commerce store owners")
- Platform focus (optional) — prioritize specific platforms (YouTube, X/Twitter, Newsletters, Podcasts, Instagram). Default: search all.
- Minimum follower count (optional) — exclude influencers below a threshold. Default: no minimum (micro-influencers included).
Extract from inputs:
- Niche keywords: The 3-5 topic terms that define the industry
- Audience profile: Who the target audience is (role, stage, problem domain)
- Platform priorities: Which platforms to weight more heavily
Step 2: Generate Search Queries#
Generate 10 search queries to surface influencers across platform types and discovery angles:
"Top influencers" list queries:
- "top [niche] influencers [current year]"
- "best [niche] creators to follow"
- "top [audience] thought leaders"
Platform-specific queries:
- "top [niche] youtube channels"
- "[niche] youtube [subscribers OR creators]"
- "best [niche] newsletter substack"
- "top [niche] podcast"
- "[niche] twitter thought leaders"
Cross-platform discovery:
- "[niche] conference speakers [current year]"
- "who sponsors [niche] newsletters"
- "[niche] podcast guest list"
Step 3: Search YouTube#
Search YouTube for top channels in the niche:
- Use queries: "top [niche] YouTube channels", "[audience] YouTube", "[niche keyword] tutorial/advice channel"
- For each channel found, collect: Channel name, URL, subscriber count, content focus
- Aim for 20-30 YouTube channels across macro (500k+), mid-tier (50k-500k), and micro (<50k) tiers
Step 4: Search X/Twitter#
Search for thought leaders on X/Twitter:
- Use queries: "[niche] twitter", "best [niche] accounts to follow", "[identity/role] twitter"
- Check "listicles" — blog posts titled "Best [niche] accounts to follow on Twitter/X" often list 10-20 accounts at once
- Include both prolific posters (daily content) and respected practitioners (less frequent but high-quality takes)
Step 5: Search Blogs, Newsletters, and Podcasts#
Blogs#
- Search: "top [niche] blogs", "best [niche] blog to read", "[niche] writers"
- Look for independent writers with their own sites
Newsletters#
- Search: "best [niche] newsletter", "[niche] substack", "[niche] email newsletter"
- Check Substack's discover page for the niche if applicable
Podcasts#
- Search: "top [niche] podcast", "best [niche] podcast", "[audience] podcast"
- Check Apple Podcasts and Spotify charts if accessible
Step 6: Search Meta (Facebook and Instagram)#
- Search: "[niche] facebook page", "[identity] instagram", "[niche] instagram creator"
- Focus on public profiles and pages
- Meta is lower priority for most B2B niches — if the niche skews consumer or visual, prioritize more heavily
Step 7: Mine Cross-Platform Discovery Sources#
Conference Speaker Lists#
- Search: "[niche] conference [current year] speakers", "[niche] summit speakers"
- Conference keynote and session speakers are pre-vetted as recognized voices
- Extract speaker names → find their primary platform
Podcast Guest Cross-References#
- Search: "[top podcast in niche] guests", "most popular [niche] podcast episodes"
- Repeat guests on multiple podcasts = high-credibility signal
Newsletter Curator Lists#
- Search: "who sponsors [niche] newsletters", "[niche] newsletter sponsors"
- Companies sponsoring newsletters indicate which newsletters have a commercially valuable audience
Step 8: Normalize All Results#
Compile all discovered influencers into a single list. For each entry, record:
| Field | Description |
|---|---|
| Name | Person or brand name |
| Primary Platform | The platform where they have the largest/most active presence |
| X/Twitter URL | Profile URL or "—" |
| YouTube URL | Channel URL or "—" |
| Newsletter/Blog URL | URL or "—" |
| Podcast URL | URL or "—" |
| Instagram/Facebook URL | URL or "—" |
| Primary Follower Count | Count on their primary platform |
| Content Type | What they primarily create (tutorials, opinion/takes, case studies, interviews, tools) |
| Source | Where they were discovered |
Deduplication: If the same person appears from multiple discovery sources, merge into one entry. Multiple discovery sources = stronger relevance signal.
Step 9: Score Each Influencer#
Score every influencer on Relevance (1–5):
| Score | Signal |
|---|---|
| 5 | Content is directly about the target audience's core problems — almost every post/video is on-target |
| 4 | Strong match — most content is relevant, occasional tangents |
| 3 | Adjacent — their niche overlaps meaningfully but isn't a perfect match |
| 2 | Loose match — some relevant content but audience is broader or different |
| 1 | Tangential — topic surface-level overlap but different audience |
Audience Overlap Rating#
| Rating | Criteria |
|---|---|
| High | Relevance ≥ 4 |
| Medium | Relevance = 3 |
| Low | Relevance ≤ 2 |
Step 10: Sort and Finalize#
Sort the full list:
- Primary: Audience Overlap rating (High → Medium → Low)
- Secondary: Primary follower count (largest first within each tier)
Include micro-influencers (1K–50K followers) alongside macro — do not exclude them.
Output Format#
# Influencer Discovery: [Industry/Niche]
**Date:** [current date]
**Industry/Niche:** [description]
**Target Audience:** [description]
**Influencers found:** [count] across [X] platforms
**Audience Overlap breakdown:** High: [X] | Medium: [X] | Low: [X]
---
## High Overlap Influencers
| # | Name | Primary Platform | Followers | X/Twitter | YouTube | Newsletter/Blog | Podcast | Instagram/FB | Content Type | Discovery Source |
|---|------|-----------------|-----------|-----------|---------|-----------------|---------|-------------|-------------|-----------------|
| 1 | [name] | [platform] | [count] | [url or —] | [url or —] | [url or —] | [url or —] | [url or —] | [type] | [source] |
---
## Medium Overlap Influencers
[Same table structure]
---
## Low Overlap Influencers
[Same table structure]
---
## Platform Coverage Summary
| Platform | Count | High Overlap | Notes |
|----------|-------|-------------|-------|
| X/Twitter | X | X | [observation] |
| YouTube | X | X | |
| Newsletter/Blog | X | X | |
| Podcast | X | X | |
| Instagram/Facebook | X | X | |
---
## Observations
[2-3 bullet points: where this niche's influencer ecosystem is concentrated, tier distribution, notable patterns]
## Partnership Opportunities
[Top 3-5 influencers worth prioritizing for sponsorship or collaboration, with a 1-sentence reason each]
## Recommended Next Steps
1. [e.g., "Reach out to top 3 High Overlap newsletter authors — newsletter sponsorships often have fastest lead time"]
2. [e.g., "Monitor [top X/Twitter account] for mentions of problems your product solves"]Rules#
- Aim for 100+ influencers total. For narrow B2B niches, 50 is acceptable — flag it.
- Never invent influencer accounts or inflate follower counts — only include verified results from search.
- Never exclude micro-influencers (1K–50K) — they are often the highest-value partnerships for niche B2B audiences.
- Never focus only on one platform — cross-platform coverage is a core output requirement.
- Discovery source matters: an influencer found via conference speakers + podcast guest + YouTube search is more credible than one found via a single listicle.
- Follower counts are best-effort estimates — verify before outreach.
- If fewer than 30 influencers are found, try broader synonyms for the niche or audience.
FAQ
07 QUESTIONS
01What is the Influencer discovery agent skill?
Use when finding influencers to partner with for sponsorships, affiliate deals, or co-marketing. It is listed under social media in the 100xLab agent skills directory.
02How do I install Influencer discovery in Cursor, Claude Code, or Codex?
Run npx skills add superamped/ai-marketing-skills --skill influencer-discovery in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only Influencer discovery, not every skill in the repository.
03What does the Influencer discovery SKILL.md cover?
The SKILL.md includes sections on Usage, Process, Step 1: Gather Inputs, Step 2: Generate Search Queries, Step 3: Search YouTube and Step 4: Search X/Twitter. Read the full text on this page or in plain markdown at /resources/agent-skills/superamped-ai-marketing-skills--influencer-discovery--1b7qpi4/raw.
04Which agents can use Influencer discovery?
Influencer discovery installs with the cross-agent skills installer (npx skills add), which sets it up for agents such as Claude Code, Cursor and Codex. Each agent loads the SKILL.md when you ask for the skill by name.
05What license is Influencer discovery under?
The superamped/ai-marketing-skills repository declares the MIT license. Read the license file in the repository before you copy or redistribute the skill.
06Is Influencer discovery free to use?
Reading, copying and installing Influencer discovery costs nothing: it is published in a public GitHub repository under the MIT license. Reuse and redistribution follow that license.
07Where is the source of Influencer discovery?
Influencer discovery comes from https://github.com/superamped/ai-marketing-skills, which has 49 GitHub stars. The SKILL.md is at https://github.com/superamped/ai-marketing-skills/blob/HEAD/skills/research/influencer-discovery/SKILL.md. The author is superamped.
Need an agent workflow built around your stack?
Tell us the workflow you want automated. We reply within 4 working hours (IST).
ATTRIBUTION
Influencer discovery was written by its original authors and is published in superamped/ai-marketing-skills (opens GitHub in a new tab) under the MIT license. All rights stay with the original authors.
100xLab did not write, maintain or endorse this skill. This page lists it for discovery. Repo stars belong to the source repository, not to the skill. Review any skill before you install it.