gooseworks-ai/gtm-enrichment-deep
AI-agent-powered lead enrichment using Sixtyfour as primary source. Takes an email (+ optional name) and returns comprehensive person + company data with funding, AI/B2B classification, and full error visibility. Higher cost (~$0.20/lead) but simpler architecture.
npx skills add https://github.com/gooseworks-ai/goose-skills --skill gtm-enrichment-deepRead your credentials from ~/.gooseworks/credentials.json:
export GOOSEWORKS_API_KEY=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json'))['api_key'])")
export GOOSEWORKS_API_BASE=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json')).get('api_base','https://api.gooseworks.ai'))")
If ~/.gooseworks/credentials.json does not exist, tell the user to run: npx gooseworks login
All endpoints use Bearer auth: -H "Authorization: Bearer $GOOSEWORKS_API_KEY"
Enrich a lead from an email address (+ optional name) using Sixtyfour's AI agents as the primary enrichment source. Returns person data, company data, funding history, and AI/B2B classification.
Cost: ~$0.20-$0.22 per lead
Latency: ~30-60s (Sixtyfour AI agents browse the web)
Required:
[email protected])Optional:
Extract the domain from the email address. Example: [email protected] -> domain: acme.com
Fire both calls simultaneously. These are the primary data sources.
Enrich Lead ($0.10):
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"sixtyfour","path":"/enrich-lead"}'
"lead_info": {
"email": "{email}",
"first_name": "{first_name_if_known}",
"last_name": "{last_name_if_known}",
"company": "{company_name_if_known}",
"domain": "{domain}"
},
"struct": {
"full_name": "Full legal name of this person",
"first_name": "First name",
"last_name": "Last name",
"title": "Current job title at their company",
"linkedin_url": "LinkedIn profile URL (full URL starting with https://linkedin.com/in/)",
"city": "City where the person is located",
"state": "State or region where the person is located",
"country": "Country where the person is located"
}
}'
Enrich Company ($0.10):
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"sixtyfour","path":"/enrich-company"}'
"target_company": {
"domain": "{domain}"
},
"struct": {
"company_name": "Official company name",
"description": "One-paragraph description of what the company does",
"linkedin_url": "LinkedIn company page URL (full URL starting with https://linkedin.com/company/)",
"hq_city": "Headquarters city",
"hq_state": "Headquarters state or region",
"hq_country": "Headquarters country",
"employee_count": "Approximate number of employees (number only)",
"founded_year": "Year the company was founded (number only)",
"total_funding_amount_usd": "Total funding raised in USD (number only, no $ sign)",
"latest_funding_date": "Date of most recent funding round (YYYY-MM-DD format)",
"latest_funding_stage": "Stage of most recent funding round (e.g., Series A, Series B, Seed)",
"latest_funding_amount_usd": "Amount raised in most recent round in USD (number only)",
"is_ai_company": "true or false - does this company build or primarily use AI/ML technology?",
"ai_evidence": "Brief explanation of why this is or is not an AI company",
"is_b2b_saas": "true or false - is this a B2B SaaS company?",
"b2b_evidence": "Brief explanation of why this is or is not B2B SaaS"
}
}'
Record the status, latency, and any errors for both calls.
ONLY run if Sixtyfour /enrich-lead did NOT return a LinkedIn URL.
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"apollo","path":"/api/v1/people/match"}'
"email": "{email}",
"reveal_personal_emails": true
}'
Cost: $0.01. Extract linkedin_url, and also grab name, title, organization as cross-reference data.
ONLY run if Sixtyfour /enrich-company did NOT return funding data (total_funding_amount_usd is null/empty).
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"apollo","path":"/api/v1/organizations/enrich","query":{"domain":"{domain}"}}'
Cost: $0.01. Extract funding events, total funding, latest funding stage, and latest funding amount.
Merge all data into the output format below. Apply these rules:
sixtyfour or apollohigh — Sixtyfour returned the field directlymedium — Apollo fallback provided the fieldlow — field was inferred or partially matchedPresent the results as a JSON code block:
{
"person": {
"full_name": "string",
"title": "string",
"linkedin_url": "string",
"location": {"city": "string", "state": "string", "country": "string"},
"email_verified": "unknown",
"confidence": "high | medium | low",
"source": "sixtyfour | apollo"
},
"company": {
"name": "string",
"domain": "string",
"linkedin_url": "string",
"description": "string",
"geo": {"city": "string", "state": "string", "country": "string"},
"employee_count": "number | null",
"founded_year": "number | null",
"funding": {
"total_amount": "number | null",
"total_amount_printed": "string | null",
"latest_round_date": "string | null",
"latest_round_stage": "string | null",
"latest_round_amount": "number | null",
"rounds": [],
"confidence": "high | medium | low"
},
"classification": {
"is_ai": {"value": true, "confidence": "high | medium | low", "evidence": ["string"]},
"is_b2b_saas": {"value": true, "confidence": "high | medium | low", "evidence": ["string"]}
},
"buying_signals": {
"has_enterprise_plan": null,
"has_self_serve": null,
"hiring_enterprise_reps": null,
"website_traffic_rank": null,
"github_stars": null,
"tech_stack": null
},
"confidence": "high | medium | low",
"source": "sixtyfour | apollo | merged"
},
"meta": {
"total_cost": "$0.XX",
"api_calls": [],
"phases_run": [1, 2],
"enrichment_timestamp": "ISO datetime"
}
}
Track EVERY API call in the meta.api_calls array:
{
"api": "sixtyfour",
"endpoint": "/enrich-lead",
"status": "success | partial | error",
"cost": "$0.10",
"latency_ms": 35000,
"fields_returned": ["full_name", "title", "linkedin_url"],
"fields_missing": ["city"],
"error": null
}
If an API call fails, returns empty data, or times out, include it in the api_calls array with status='error' and a clear error message. Never silently skip failures.
Sum all API call costs and report in meta.total_cost:
Input: [email protected]
Expected flow:
acme.comstruct field in Sixtyfour tells the AI agent exactly what to research — modify fields there if you need different data pointsTake gooseworks-ai/gtm-enrichment-deep from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npx.
Without those the skill loads but fails at the first command.