apify-lead-generation

Scrape leads from multiple platforms using Apify Actors.

38 stars

Best use case

apify-lead-generation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Scrape leads from multiple platforms using Apify Actors.

Teams using apify-lead-generation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/apify-lead-generation/SKILL.md --create-dirs "https://raw.githubusercontent.com/lingxling/awesome-skills-cn/main/antigravity-awesome-skills/plugins/antigravity-awesome-skills-claude/skills/apify-lead-generation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/apify-lead-generation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How apify-lead-generation Compares

Feature / Agentapify-lead-generationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Scrape leads from multiple platforms using Apify Actors.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Lead Generation

Scrape leads from multiple platforms using Apify Actors.

## When to Use
- You need business, creator, or contact leads from maps, search, social, or video platforms.
- The task involves selecting an Apify Actor to discover prospects and extract outreach data.
- You need exported lead data plus a concise summary of lead quality or segmentation.

## Prerequisites
(No need to check it upfront)

- `.env` file with `APIFY_TOKEN`
- Node.js 20.6+ (for native `--env-file` support)
- `mcpc` CLI tool: `npm install -g @apify/mcpc`

## Workflow

Copy this checklist and track progress:

```
Task Progress:
- [ ] Step 1: Determine lead source (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the lead finder script
- [ ] Step 5: Summarize results
```

### Step 1: Determine Lead Source

Select the appropriate Actor based on user needs:

| User Need | Actor ID | Best For |
|-----------|----------|----------|
| Local businesses | `compass/crawler-google-places` | Restaurants, gyms, shops |
| Contact enrichment | `vdrmota/contact-info-scraper` | Emails, phones from URLs |
| Instagram profiles | `apify/instagram-profile-scraper` | Influencer discovery |
| Instagram posts/comments | `apify/instagram-scraper` | Posts, comments, hashtags, places |
| Instagram search | `apify/instagram-search-scraper` | Places, users, hashtags discovery |
| TikTok videos/hashtags | `clockworks/tiktok-scraper` | Comprehensive TikTok data extraction |
| TikTok hashtags/profiles | `clockworks/free-tiktok-scraper` | Free TikTok data extractor |
| TikTok user search | `clockworks/tiktok-user-search-scraper` | Find users by keywords |
| TikTok profiles | `clockworks/tiktok-profile-scraper` | Creator outreach |
| TikTok followers/following | `clockworks/tiktok-followers-scraper` | Audience analysis, segmentation |
| Facebook pages | `apify/facebook-pages-scraper` | Business contacts |
| Facebook page contacts | `apify/facebook-page-contact-information` | Extract emails, phones, addresses |
| Facebook groups | `apify/facebook-groups-scraper` | Buying intent signals |
| Facebook events | `apify/facebook-events-scraper` | Event networking, partnerships |
| Google Search | `apify/google-search-scraper` | Broad lead discovery |
| YouTube channels | `streamers/youtube-scraper` | Creator partnerships |
| Google Maps emails | `poidata/google-maps-email-extractor` | Direct email extraction |

### Step 2: Fetch Actor Schema

Fetch the Actor's input schema and details dynamically using mcpc:

```bash
export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"
```

Replace `ACTOR_ID` with the selected Actor (e.g., `compass/crawler-google-places`).

This returns:
- Actor description and README
- Required and optional input parameters
- Output fields (if available)

### Step 3: Ask User Preferences

Before running, ask:
1. **Output format**:
   - **Quick answer** - Display top few results in chat (no file saved)
   - **CSV** - Full export with all fields
   - **JSON** - Full export in JSON format
2. **Number of results**: Based on character of use case

### Step 4: Run the Script

**Quick answer (display in chat, no file):**
```bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'
```

**CSV:**
```bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.csv \
  --format csv
```

**JSON:**
```bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.json \
  --format json
```

### Step 5: Summarize Results

After completion, report:
- Number of leads found
- File location and name
- Key fields available
- Suggested next steps (filtering, enrichment)

## Error Handling

`APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`
`mcpc not found` - Ask user to install `npm install -g @apify/mcpc`
`Actor not found` - Check Actor ID spelling
`Run FAILED` - Ask user to check Apify console link in error output
`Timeout` - Reduce input size or increase `--timeout`

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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