onboarding-kickoff
Automated client onboarding after kickoff call - generates leads, creates email campaigns, sets up auto-reply. Use when user asks to onboard a new client, set up campaigns for client, or run post-kickoff automation.
Best use case
onboarding-kickoff is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Automated client onboarding after kickoff call - generates leads, creates email campaigns, sets up auto-reply. Use when user asks to onboard a new client, set up campaigns for client, or run post-kickoff automation.
Teams using onboarding-kickoff 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/onboarding-kickoff/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How onboarding-kickoff Compares
| Feature / Agent | onboarding-kickoff | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Automated client onboarding after kickoff call - generates leads, creates email campaigns, sets up auto-reply. Use when user asks to onboard a new client, set up campaigns for client, or run post-kickoff automation.
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
# Post-Kickoff Client Onboarding
## Goal
Automated onboarding workflow that runs after kickoff call. Generates leads, creates campaigns, and sets up auto-reply system.
## Inputs (from kickoff call)
**Required:**
- `client_name`: Company name
- `client_email`: Primary contact email
- `service_type`: What service they provide
- `target_location`: Geographic area
- `offers`: Three offers (pipe-separated)
- `target_audience`: Who they're targeting
- `social_proof`: Credentials/results
**Optional:**
- `lead_limit`: Number of leads (default: 500)
- `value_proposition`: Additional context
## Scripts
- `./scripts/gmaps_lead_pipeline.py` - Lead generation
- `./scripts/casualize_company_names_batch.py` - Name casualization
- `./scripts/instantly_create_campaigns.py` - Campaign creation
- `./scripts/onboarding_post_kickoff.py` - Full orchestration
- `./scripts/update_sheet.py` - Sheet updates
## Process
### Step 1: Generate Lead Search Query
Format: `{service_type} in {target_location}`
Example: "plumbers in Austin TX"
### Step 2: Scrape and Enrich Leads
```bash
python3 ./scripts/gmaps_lead_pipeline.py \
--search "{service_type} in {target_location}" \
--limit {lead_limit} \
--sheet-name "{client_name} - Leads" \
--workers 5
```
### Step 3: Casualize Company Names
```bash
python3 ./scripts/casualize_company_names_batch.py \
--sheet-url "{sheet_url}" \
--column "business_name" \
--output-column "casualCompanyName"
```
### Step 4: Create Instantly Campaigns
```bash
python3 ./scripts/instantly_create_campaigns.py \
--client_name "{client_name}" \
--client_description "..." \
--offers "{offers}" \
--target_audience "{target_audience}" \
--social_proof "{social_proof}"
```
### Step 5: Upload Leads to Campaigns
Distribute leads evenly across 3 campaigns via Instantly API.
### Step 6: Add Knowledge Base Entry
Add entry to auto-reply knowledge base sheet for intelligent response handling.
### Step 7: Send Summary Email
Send completion email to client with:
- Campaign links and leads counts
- Lead spreadsheet URL
- Auto-reply configuration details
- Next steps
## Output
```json
{
"status": "success",
"client_name": "...",
"sheet_url": "...",
"lead_count": 50,
"campaigns": [...],
"leads_uploaded": true,
"knowledge_base_updated": true,
"summary_email_sent": true
}
```
## Timing
- Full workflow: ~10-15 minutes for 50 leads
- Lead scraping uses 5 workers by default
## Error Handling
- < 10 leads found: Warn but continue
- 0 leads found: Error (bad search query)
- Instantly API error: Capture, note for manual fix
- Sheet/email failures: Log but complete workflow
---
## Schema
### Inputs
| Name | Type | Required | Description |
|------|------|----------|-------------|
| `client_name` | string | Yes | Company name |
| `client_email` | string | Yes | Primary contact email |
| `service_type` | string | Yes | What service they provide |
| `target_location` | string | Yes | Geographic area |
| `offers` | string | Yes | Three offers (pipe-separated) |
| `target_audience` | string | Yes | Who they're targeting |
| `social_proof` | string | Yes | Credentials/results |
| `lead_limit` | integer | No | Number of leads (default: 500) |
### Outputs
| Name | Type | Description |
|------|------|-------------|
| `status` | string | success/failure |
| `sheet_url` | string | Lead spreadsheet URL |
| `lead_count` | integer | Number of leads generated |
| `campaigns` | array | Campaign IDs created |
| `summary_email_sent` | boolean | Whether summary was emailed |
### Credentials
| Name | Source |
|------|--------|
| `APIFY_API_TOKEN` | .env |
| `ANTHROPIC_API_KEY` | .env |
| `INSTANTLY_API_KEY` | .env |
### Composable With
Skills that chain well with this one: `gmaps-leads`, `casualize-names`, `instantly-campaigns`, `welcome-email`
### Cost
~$5-10 for 500 leads + campaignsRelated Skills
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