create-image-fal
Generate or edit an image via any FAL image model (nano-banana edit, gpt-image, flux, ...), ROUTED THROUGH THE fal-proxy so it bills the Ads agent. image_urls…
Qualifies inbound leads against full ICP criteria — company size, industry, use case fit, role/seniority of the person. Checks CRM and existing customer base for duplicates and existing relationships. Outputs a scored CSV with qualification status, reasoning, and pipeline
$ npx -y skills add gooseworks-ai/goose-skills --skill inbound-lead-qualification --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/inbound-lead-qualificationContext preview
The summary Claude sees to decide when to auto-load this skill.
Qualifies inbound leads against full ICP criteria — company size, industry, use case fit, role/seniority of the person. Checks CRM and existing customer base for duplicates and existing relationships. Outputs a scored CSV with qualification status, reasoning, and pipeline
name: inbound-lead-qualification version: 1.0.0 description: > Qualifies inbound leads against full ICP criteria — company size, industry, use case fit, role/seniority of the person. Checks CRM and existing customer base for duplicates and existing relationships. Outputs a scored CSV with qualification status, reasoning, and pipeline overlap flags. Tool-agnostic — works with any CRM, enrichment tool, or data source. tags: [lead-generation]
Takes a set of inbound leads and validates each against your full ICP criteria. Not a fast-pass triage (that's `inbound-lead-triage`) — this is the thorough qualification step that determines whether a lead is genuinely worth pursuing, and produces a scored CSV for the team.
Load this composite when:
[Inbound Leads] → Step 1: Load ICP & Config → Step 2: CRM/Pipeline Check → Step 3: Company Qualification → Step 4: Person Qualification → Step 5: Use Case Fit → Step 6: Score & Verdict → Step 7: Output CSV
---
On first run, establish the ICP definition and CRM access. Save to the current working directory or wherever the user prefers (e.g., `config/lead-qualification.json`).
{
"icp_definition": {
"company_size": {
"min_employees": null,
"max_employees": null,
"sweet_spot": "",
"notes": ""
},
"industry": {
"target_industries": [],
"excluded_industries": [],
"notes": ""
},
"use_case": {
"primary_use_cases": [],
"secondary_use_cases": [],
"anti_use_cases": [],
"notes": ""
},
"company_stage": {
"target_stages": [],
"excluded_stages": [],
"notes": ""
},
"geography": {
"target_regions": [],
"excluded_regions": [],
"notes": ""
}
},
"buyer_personas": [
{
"name": "",
"titles": [],
"seniority_levels": [],
"departments": [],
"is_economic_buyer": false,
"is_champion": false,
"is_user": false
}
],
"hard_disqualifiers": [],
"hard_qualifiers": [],
"crm_access": {
"tool": "HubSpot | Salesforce | CSV export | none",
"access_method": "",
"tables_or_objects": []
},
"existing_customer_source": {
"tool": "HubSpot | Salesforce | CSV | none",
"access_method": ""
},
"qualification_prompt_path": "path/to/lead-qualification/prompt.md or null"
}**If `lead-qualification` capability already has a saved qualification prompt:** Reference it directly — don't rebuild ICP criteria from scratch.
**On subsequent runs:** Load config silently.
---
1. Load the client's ICP config (or qualification prompt from `lead-qualification` capability) 2. Parse the inbound lead list — accept any format:
3. Identify what data is available vs. missing per lead:
If >50% of leads are missing critical fields (company name or person title), recommend running `inbound-lead-enrichment` first. Ask: "Many leads are missing company/title data. Want me to enrich them first, or qualify with what's available?"
---
For each lead, check against existing data sources to identify overlaps:
**Check 1 — Existing customer?**
**Check 2 — Already in pipeline?**
**Check 3 — Previous engagement?**
**Check 4 — Known from signal composites?**
Each lead tagged with:
---
For each lead's company, evaluate against every ICP company dimension:
**Dimension 1 — Company Size**
Put your AI agent on the growth team. Research customers and competitors, analyze what is working, create the next campaign, and learn from the result.
Repo: gooseworks-ai/goose-skills
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