# Influencer Discovery

> Discovers and compiles lists of relevant influencers across platforms based on niche, audience demographics, content style, and brand fit. The foundation of any successful influencer marketing program.

- **Type:** Skill
- **Install:** `agentstack add skill-lemonhall-influencer-marketing-claude-skills-influencer-discovery`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [lemonhall](https://agentstack.voostack.com/s/lemonhall)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** Apache-2.0
- **Upstream author:** [lemonhall](https://github.com/lemonhall)
- **Source:** https://github.com/lemonhall/influencer-marketing-claude-skills/tree/main/map/influencer-discovery

## Install

```sh
agentstack add skill-lemonhall-influencer-marketing-claude-skills-influencer-discovery
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Influencer Discovery

This skill helps you find the right influencers for your brand by searching across platforms, analyzing content and audience fit, and building curated lists of potential partners. It adapts traditional lead research methodology to the influencer marketing context.

## When to Use This Skill

- Building an influencer roster from scratch
- Expanding into new platforms or niches
- Finding replacements for churned influencer partners
- Discovering micro and nano influencers at scale
- Identifying competitors' influencer partners
- Building an always-on influencer pipeline

## What This Skill Does

1. **Multi-Platform Search**: Finds influencers across Instagram, TikTok, YouTube, Twitter, etc.
2. **Criteria Matching**: Filters by niche, follower count, engagement, location
3. **Audience Analysis**: Evaluates if their audience matches your target
4. **Content Assessment**: Reviews content quality and style fit
5. **Authenticity Screening**: Identifies potential red flags
6. **List Building**: Compiles organized, actionable influencer lists

## How to Use

### Basic Discovery

```
Find 20 influencers in [niche] for [brand/product]
```

```
Discover micro-influencers (10K-50K followers) in [category] on [platform]
```

### With Specific Criteria

```
Find influencers who:
- Are in the [niche] space
- Have 50K-200K followers
- Post primarily on TikTok and Instagram
- Are based in [location]
- Have engagement rates above 4%
- Have worked with brands similar to [brand]
```

### From Competitor Analysis

```
Who are the influencers partnering with [competitor]?
```

## Instructions

When a user requests influencer discovery:

1. **Define Search Criteria**

   ```markdown
   ### Discovery Parameters
   
   **Brand/Product**: [name]
   **Campaign Goal**: [awareness/consideration/conversion]
   **Budget Range**: [budget implications for influencer tier]
   
   **Search Criteria**:
   
   | Parameter | Requirement | Priority |
   |-----------|-------------|----------|
   | Niche/Category | [niche] | Required |
   | Platform(s) | [platforms] | Required |
   | Follower Range | [min-max] | Required |
   | Engagement Rate | [minimum %] | Required |
   | Location | [regions] | [Required/Preferred] |
   | Language | [languages] | [Required/Preferred] |
   | Content Type | [video/photo/etc.] | Preferred |
   | Posting Frequency | [minimum] | Preferred |
   | Audience Demographics | [age/gender/interests] | Preferred |
   | Brand Safety | [requirements] | Required |
   
   **Nice-to-Have**:
   - [Additional preference 1]
   - [Additional preference 2]
   
   **Exclusions**:
   - [Competitor partnerships]
   - [Content types to avoid]
   - [Other exclusions]
   ```

2. **Conduct Search**

   ```markdown
   ## Search Strategy
   
   ### Primary Search Methods
   
   1. **Hashtag Research**
      - Core hashtags: #[hashtag1], #[hashtag2]
      - Niche hashtags: #[hashtag3], #[hashtag4]
      - Brand-adjacent: #[hashtag5]
   
   2. **Similar Accounts**
      - Starting from: @[known influencer]
      - Platform suggestions: "Similar to" features
   
   3. **Competitor Mentions**
      - Check tagged posts on [competitor accounts]
      - Monitor #[competitor hashtags]
   
   4. **Platform-Specific Discovery**
      - TikTok: Creator Marketplace, trending sounds
      - Instagram: Explore page, Reels
      - YouTube: Related channels, collaboration networks
   
   5. **Tool Queries** (if available)
      - [Platform]: [search query]
   ```

3. **Initial Screening**

   ```markdown
   ## Initial Candidate Pool
   
   **Total Candidates Found**: [number]
   **After Initial Screening**: [number]
   
   ### Screening Criteria Applied
   
   | Criterion | Filter | Eliminated |
   |-----------|--------|------------|
   | Follower range | [range] | [#] |
   | Engagement rate | >[%] | [#] |
   | Recent activity | 30 days
   ```

4. **Build Influencer Profiles**

   For each qualified influencer:

   ```markdown
   ---
   
   ## Influencer #[X]: @[handle]
   
   ### Basic Information
   
   | Attribute | Details |
   |-----------|---------|
   | **Name** | [name] |
   | **Handle** | @[handle] |
   | **Platform** | [primary platform] |
   | **Other Platforms** | [other handles] |
   | **Location** | [city, country] |
   | **Language** | [primary language] |
   | **Niche** | [category] |
   
   ### Metrics
   
   | Platform | Followers | Engagement Rate | Avg. Views |
   |----------|-----------|-----------------|------------|
   | [Platform 1] | [count] | [%] | [views] |
   | [Platform 2] | [count] | [%] | [views] |
   
   **Growth Trend**: [growing/stable/declining] ([%] last 90 days)
   
   ### Audience Analysis
   
   | Demographic | Breakdown | Notes |
   |-------------|-----------|-------|
   | Gender | [%F / %M] | |
   | Age | [primary age range] | |
   | Location | [top countries/cities] | |
   | Interests | [categories] | |
   
   **Audience Quality Score**: [X/10]
   - Real followers estimate: [%]
   - Audience-brand overlap: [High/Medium/Low]
   
   ### Content Analysis
   
   **Content Style**:
   - Primary format: [format]
   - Posting frequency: [X posts/week]
   - Aesthetic: [description]
   - Tone: [description]
   
   **Top Performing Content**:
   1. [Content 1]: [engagement]
   2. [Content 2]: [engagement]
   3. [Content 3]: [engagement]
   
   **Brand Fit Assessment**:
   - Visual alignment: [High/Medium/Low]
   - Value alignment: [High/Medium/Low]
   - Audience alignment: [High/Medium/Low]
   
   ### Partnership History
   
   **Past Brand Partnerships**:
   | Brand | Date | Content Type | Est. Performance |
   |-------|------|--------------|------------------|
   | [brand 1] | [date] | [type] | [performance] |
   | [brand 2] | [date] | [type] | [performance] |
   
   **Competitor Partnerships**: [Yes/No - details]
   
   ### Contact Information
   
   - **Email**: [if public]
   - **Agency/Manager**: [if applicable]
   - **Contact Method**: [best approach]
   
   ### Fit Score Summary
   
   | Factor | Score (1-5) |
   |--------|-------------|
   | Audience match | [score] |
   | Content quality | [score] |
   | Brand alignment | [score] |
   | Engagement quality | [score] |
   | Authenticity | [score] |
   | **Total** | **[X/25]** |
   
   **Recommendation**: ⭐ [Highly Recommended / Recommended / Consider / Pass]
   
   **Why They're a Good Fit**:
   [2-3 sentences explaining the fit]
   
   **Potential Concerns**:
   - [Concern 1 if any]
   
   ---
   ```

5. **Compile Discovery List**

   ```markdown
   # Influencer Discovery Results
   
   **Search Date**: [date]
   **Brand/Campaign**: [name]
   **Criteria Used**: [summary]
   
   ## Summary Statistics
   
   | Metric | Count |
   |--------|-------|
   | Total Candidates Reviewed | [#] |
   | Passed Initial Screening | [#] |
   | Highly Recommended | [#] |
   | Recommended | [#] |
   | To Consider | [#] |
   
   ### By Platform
   
   | Platform | Count | Avg Followers | Avg ER |
   |----------|-------|---------------|--------|
   | Instagram | [#] | [avg] | [%] |
   | TikTok | [#] | [avg] | [%] |
   | YouTube | [#] | [avg] | [%] |
   
   ### By Tier
   
   | Tier | Follower Range | Count | Est. Cost Range |
   |------|----------------|-------|-----------------|
   | Mega | 1M+ | [#] | [range] |
   | Macro | 100K-1M | [#] | [range] |
   | Micro | 10K-100K | [#] | [range] |
   | Nano | 5%) for key content
- 7 mid-tier for volume and variety  
- 3 rising stars for early partnership potential

**Next Steps**: Run through fit-scorer for final ranking, begin outreach to top 5.
```

## Tips for Success

1. **Quality over quantity** - Better to have 10 perfect fits than 100 maybes
2. **Verify authenticity** - Check for fake followers, engagement pods
3. **Review recent content** - Ensure consistent quality and brand safety
4. **Consider past partnerships** - Learn from their collaboration history
5. **Look beyond followers** - Engagement quality matters more
6. **Check all platforms** - Multi-platform creators offer more value
7. **Save for later** - Build a pipeline, not just campaign lists

## Related Skills

- [audience-analyzer](../../insight/audience-analyzer/) - Define who to reach
- [fit-scorer](../fit-scorer/) - Score and rank discovered influencers
- [competitor-tracker](../competitor-tracker/) - Find competitor influencers
- [outreach-manager](../../activate/outreach-manager/) - Contact discovered influencers

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [lemonhall](https://github.com/lemonhall)
- **Source:** [lemonhall/influencer-marketing-claude-skills](https://github.com/lemonhall/influencer-marketing-claude-skills)
- **License:** Apache-2.0

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-lemonhall-influencer-marketing-claude-skills-influencer-discovery
- Seller: https://agentstack.voostack.com/s/lemonhall
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.
