Sixtyfour Skill

People and company intelligence via the Sixtyfour AI API. AI research agents that read the live web — not static databases — to return structured, confidence...

Security Scan

The skill appears to implement a people/company enrichment integration, but its runtime instructions and registry metadata are inconsistent (notably a missing declared API key) and the skill can deliver enriched PII to external webhooks — review before installing.

Purpose & Capability

The SKILL.md and README clearly describe a people/company enrichment API (Sixtyfour.ai) and show curl examples that require an API key (x-api-key / SIXTYFOUR_API_KEY). However, the registry metadata lists no required environment variables or primary credential. That mismatch (the skill needs a secret but doesn't declare it) is an incoherence and should be fixed; otherwise installers may not realize they'll need to provide a sensitive API key or how it's used.

Instruction Scope

Instructions are mostly scoped to calling the external Sixtyfour API (enrich-lead, find-email, find-phone, workflows, async jobs, webhooks). They do not instruct reading local files or unrelated env vars. Two items to note: (1) async endpoints support arbitrary webhook_url values, which can forward enriched results (including emails/phones) to any external endpoint — this is expected for such APIs but is a privacy/exfiltration risk if misconfigured; (2) the SKILL.md instructs sign-up via Google and API key export, but that API key requirement was not declared in metadata.

Install Mechanism

This is an instruction-only skill with no install spec and no code files to execute, so it does not install binaries or pull external archives. README mentions helper commands (clawhub, npx sixtyfour-mcp) but no install script is included in the package — lower install risk. Confirm that your agent platform does not auto-fetch the 'npx sixtyfour-mcp' package based on the README.

Credentials

The skill requires a single API key at runtime (SIXTYFOUR_API_KEY / x-api-key) per its examples, which is proportionate for an external API integration. However, the metadata omits declaring this required environment variable/primary credential. That omission prevents automated permission prompts and auditing of required secrets. No other credentials are requested, which is appropriate.

Persistence & Privilege

The skill does not request persistent/always-on presence (always: false) and does not modify other skills. It uses standard async webhooks and polling mechanisms. Autonomous invocation is allowed (disable-model-invocation: false) which is normal; consider restricting autonomous use if you want to limit agent-initiated lookups because the skill can query PII on demand.

What to consider before installing

This skill is coherent with its stated purpose (people/company enrichment) but has some red flags to consider before installing: - Missing declared credential: The SKILL.md requires an API key (SIXTYFOUR_API_KEY) but the registry metadata does not declare any required env vars or a primary credential. Ask the publisher to add SIXTYFOUR_API_KEY to the skill's declared requirements so your agent can surface the permission request and you can audit it. - Privacy / webhook risk: Async jobs can POST results to any webhook_url you supply. Those results may contain personal emails and phone numbers. Only configure trusted webhook endpoints and verify legal/privacy compliance (e.g., GDPR) before sending PII to third parties. - Origin verification: The skill's source is listed as unknown and homepage is missing. Verify that sixtyfour.ai is the legitimate provider (check their docs and contact points) and confirm the publisher identity before trusting API keys or installing into production agents. - Billing & scope: The docs show per-email/phone costs and free-tier limits. Test with a disposable/test API key or account and monitor usage to avoid unexpected charges. - Operational controls: If you want tighter control, restrict the skill to manual/user-invocable only (avoid autonomous runs), and consider using a dedicated API key with limited quota/permissions. If the publisher provides corrected metadata (declaring the API key) and you confirm the upstream service and privacy posture, the skill's behavior is consistent with its purpose; until then proceed cautiously.

Sixtyfour AI — People & Company Intelligence

AI research agents that investigate people and companies across the live web, returning structured, confidence-scored data. 93% accuracy — benchmarked against Clay (66%), Apollo (72%), and ZoomInfo.

Base URL: https://api.sixtyfour.ai
Auth header: x-api-key: YOUR_API_KEY (all requests)
Free tier: 50 deep researches on signup — app.sixtyfour.ai (Google sign-in, API key available immediately)
Docs: docs.sixtyfour.ai
OpenAPI spec: api.sixtyfour.ai/openapi.json

Setup

# 1. Sign up at https://app.sixtyfour.ai (Google sign-in)
# 2. Sidebar → Keys → Create new key
export SIXTYFOUR_API_KEY="your_key_here"

API Quick Reference

Endpoint	Method	Description	Sync/Async
/enrich-lead	POST	Full person profile from name + company	Both
/enrich-company	POST	Deep company research + people discovery	Both
/find-email	POST	Professional ($0.05) or personal ($0.20) email	Both
/find-phone	POST	Phone number discovery	Both
/qa-agent	POST	Score/qualify leads against custom criteria	Both
/search/start-deep-search	POST	Find people/companies via natural language	Async
/search/start-filter-search	POST	Structured filter search (skips LLM parsing)	Sync
/workflows/run	POST	Execute batch enrichment pipelines	Async

All enrichment endpoints have async variants (append -async) returning task_id for polling via GET /job-status/{task_id}. Use async for production workloads.

---

Enrich Lead

The core endpoint. Give it a name — get back a full profile with any fields you define.

curl -X POST "https://api.sixtyfour.ai/enrich-lead" \
  -H "x-api-key: $SIXTYFOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "lead_info": {
      "name": "Jane Doe",
      "company": "Acme Corp"
    },
    "struct": {
      "full_name": "Full name",
      "title": "Current job title",
      "seniority": "Seniority level (C-suite, VP, Director, Manager, IC)",
      "department": "Department or function",
      "email": "Work email address",
      "personal_email": "Personal email address",
      "phone": "Phone number",
      "linkedin": "LinkedIn profile URL",
      "location": "City and state",
      "company_name": "Current company",
      "company_size": {"description": "Approximate employee count", "type": "int"},
      "tech_stack": {"description": "Tools and technologies they use daily", "type": "list[str]"},
      "funding_stage": "Company latest funding stage and amount",
      "pain_points": {"description": "Likely challenges based on role and company stage", "type": "list[str]"},
      "social_profiles": {"description": "Twitter, GitHub, personal blog URLs", "type": "list[str]"},
      "recent_activity": "Notable recent posts, talks, or job changes"
    },
    "research_plan": "Check LinkedIn profile, company website about page, Twitter, GitHub, and any recent conference talks or blog posts."
  }'

Response

{
  "structured_data": {
    "full_name": "Jane Doe",
    "title": "VP of Engineering",
    "seniority": "VP",
    "department": "Engineering",
    "email": "[e-mail]",
    "phone": "[phone]",
    "linkedin": "https://linkedin.com/in/janedoe",
    "tech_stack": ["React", "Python", "AWS", "Terraform"],
    "funding_stage": "Series B, $45M (2025)",
    "pain_points": ["Scaling engineering team post-Series B", "Migrating legacy infrastructure"]
  },
  "notes": "Research narrative with sources...",
  "references": {
    "https://linkedin.com/in/janedoe": "LinkedIn profile",
    "https://acme.com/about": "Company about page"
  },
  "confidence_score": 9.2
}

Key Parameters

Parameter	Type	Required	Description
lead_info	object	Yes	Known data: name, company, linkedin_url, email, domain, etc.
struct	object	Yes	Fields to collect. Value is either a plain-English description string or {"description": "...", "type": "str|int|float|bool|list[str]|dict"}
research_plan	string	No	Guides where the agent looks — specific sources, methodology

Timeouts: P95 ~5 min, max ~10 min. Set client timeout to 15+ min or use /enrich-lead-async.

---

Enrich Company

Deep company research with optional people discovery.

curl -X POST "https://api.sixtyfour.ai/enrich-company" \
  -H "x-api-key: $SIXTYFOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "target_company": {
      "company_name": "Stripe",
      "website": "stripe.com"
    },
    "struct": {
      "description": "One-line company description",
      "employee_count": {"description": "Approximate headcount", "type": "int"},
      "tech_stack": {"description": "Key technologies used", "type": "list[str]"},
      "recent_funding": "Most recent funding round, amount, and date",
      "hiring_signals": {"description": "Open roles indicating growth areas", "type": "list[str]"},
      "competitors": {"description": "Main competitors", "type": "list[str]"}
    },
    "find_people": true,
    "people_focus_prompt": "Find the VP of Engineering and CTO",
    "lead_struct": {
      "name": "Full name",
      "title": "Job title",
      "linkedin": "LinkedIn URL",
      "email": "Work email"
    }
  }'

People Discovery Parameters

Parameter	Type	Description
find_people	bool	Enable people discovery at the company
people_focus_prompt	string	Describe who to find (role, department, seniority)
lead_struct	object	Fields to return per person found (same format as struct)

Each person returned includes a score (0-10) for relevance to people_focus_prompt.

---

Find Email

# Professional email ($0.05 per call)
curl -X POST "https://api.sixtyfour.ai/find-email" \
  -H "x-api-key: $SIXTYFOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "lead": {"name": "Saarth Shah", "company": "Sixtyfour AI"},
    "mode": "PROFESSIONAL"
  }'

Response: {"email": [["[e-mail]", "OK", "COMPANY"]], "cost_cents": 5}

# Personal email ($0.20 per call)
curl -X POST "https://api.sixtyfour.ai/find-email" \
  -H "x-api-key: $SIXTYFOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "lead": {"name": "Jane Doe", "company": "Acme Corp"},
    "mode": "PERSONAL"
  }'

Email field format: [["[e-mail]", "OK|UNKNOWN", "COMPANY|PERSONAL"]]

Bulk: Use /find-email-bulk-async with {"leads": [...]} for up to 100 leads.

---

Find Phone

curl -X POST "https://api.sixtyfour.ai/find-phone" \
  -H "x-api-key: $SIXTYFOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "lead": {
      "name": "John Doe",
      "company": "Example Corp",
      "linkedin_url": "https://linkedin.com/in/johndoe"
    }
  }'

Provide as much context as possible (name, company, LinkedIn, email, domain) for best hit rate.

Bulk: Use /find-phone-bulk-async for up to 100 leads, or /enrich-dataframe with CSV:

curl -X POST "https://api.sixtyfour.ai/enrich-dataframe" \
  -H "x-api-key: $SIXTYFOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"csv_data": "name,company\nJohn Doe,Example Corp", "enrichment_type": "phone"}'

---

QA Agent — Score & Qualify Leads

Evaluate enriched data against custom criteria. Returns scores and reasoning.

curl -X POST "https://api.sixtyfour.ai/qa-agent" \
  -H "x-api-key: $SIXTYFOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "data": {
      "name": "Alex Johnson",
      "title": "VP Engineering",
      "company": "TechStartup",
      "funding": "Series B",
      "tech_stack": ["React", "AWS", "PostgreSQL"]
    },
    "qualification_criteria": [
      {"criteria_name": "Seniority", "description": "VP level or above", "weight": 10.0, "threshold": 8.0},
      {"criteria_name": "Company Stage", "description": "Series A-C, actively growing", "weight": 8.0},
      {"criteria_name": "Tech Fit", "description": "Uses modern web stack", "weight": 6.0}
    ],
    "struct": {
      "overall_score": {"description": "Composite score 0-10", "type": "float"},
      "verdict": "ACCEPT or REJECT",
      "reasoning": "Why this lead does or does not qualify"
    }
  }'

Optional: add "references": [{"url": "https://...", "description": "Company blog"}] for additional context.

---

Search — Find People or Companies

Deep Search (natural language, async)

# Start search
curl -X POST "https://api.sixtyfour.ai/search/start-deep-search" \
  -H "x-api-key: $SIXTYFOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query": "VP of Engineering at Series B SaaS startups in New York", "max_results": 100}'

# Returns: {"task_id": "abc123", "status": "queued"}

# Poll (every 10-15s)
curl "https://api.sixtyfour.ai/search/deep-search-status/abc123" \
  -H "x-api-key: $SIXTYFOUR_API_KEY"

# Download results (when status = "completed", use resource_handle_id)
curl "https://api.sixtyfour.ai/search/download?resource_handle_id=xyz789" \
  -H "x-api-key: $SIXTYFOUR_API_KEY"
# Returns signed URL (expires 15 min) → CSV download

Filter Search (structured, synchronous)

curl -X POST "https://api.sixtyfour.ai/search/start-filter-search" \
  -H "x-api-key: $SIXTYFOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"filters": {"title": "VP Engineering", "location": "New York", "company_size": "50-200"}}'
# Returns: {"resource_handle_id": "...", "total_results": 150, "exported_count": 150}

---

Workflows — Batch Enrichment Pipelines

Chain blocks into reusable pipelines. Trigger via API with webhook payloads.

# List available workflow blocks
curl "https://api.sixtyfour.ai/workflows/blocks" \
  -H "x-api-key: $SIXTYFOUR_API_KEY"

# Run a workflow (webhook-triggered)
curl -X POST "https://api.sixtyfour.ai/workflows/run?workflow_id=YOUR_WORKFLOW_ID" \
  -H "x-api-key: $SIXTYFOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"webhook_payload": [{"company_name": "Acme", "website": "acme.com"}]}'

# Monitor progress (poll every 5-10s)
curl "https://api.sixtyfour.ai/workflows/runs/RUN_ID/live_status" \
  -H "x-api-key: $SIXTYFOUR_API_KEY"

# Download results
curl "https://api.sixtyfour.ai/workflows/runs/RUN_ID/results/download-links" \
  -H "x-api-key: $SIXTYFOUR_API_KEY"

Block types: webhook, read_csv, enrich_company, enrich_lead, find_email, find_phone, qa_agent

Manage workflows: GET /workflows (list), POST /workflows/create_workflow, POST /workflows/update_workflow, POST /workflows/delete_workflow

---

Webhooks — Async Notifications

Add "webhook_url" to any async request body:

{"lead_info": {...}, "struct": {...}, "webhook_url": "https://your-server.com/hook"}

Sixtyfour POSTs {task_id, status, task_type, result} on completion. 5 retries with exponential backoff.

---

Common Patterns

Signup enrichment: New user email → /enrich-lead with role, tech stack, funding fields → push to CRM
CRM backfill: Export contacts → /enrich-lead-async in parallel → poll → download enriched data
Lead scoring pipeline: /enrich-lead → /qa-agent with custom ICP criteria → route by verdict
Prospect list building: /search/start-deep-search with ICP description → CSV → /find-email per lead
Account intelligence: /enrich-company with find_people: true → weekly Slack digest of changes

---

Error Handling & Rate Limits

• Rate limit: 500 requests/min per API key
• Errors: {"error": "ErrorType", "message": "Details"}
• HTTP codes: 400 (bad request), 401 (invalid key), 429 (rate limited), 500 (retry)
• Async polling: Use GET /job-status/{task_id} — statuses: pending → processing → completed | failed

---

MCP Server

For Claude Desktop, Cursor, Windsurf, or any MCP client:

{
  "mcpServers": {
    "sixtyfour": {
      "command": "npx",
      "args": ["-y", "sixtyfour-mcp"],
      "env": {"SIXTYFOUR_API_KEY": "your_key"}
    }
  }
}

Then ask naturally: "Find the email and phone number for the CTO of Stripe" — the assistant calls Sixtyfour automatically.

---

Support: [e-mail] | docs.sixtyfour.ai | app.sixtyfour.ai