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Search for contacts (people) by role, title, seniority, location, or employer, expressed as a Search DSL query. Searches PUBLICLY AVAILABLE people data — it is NOT the user's own CRM. ## Quick Reference - **This tool**: Find TYPES of people (e.g. "engineers at Stripe", "VPs of Sales at Ramp and Brex"). - **search-contacts-by-name**: Find SPECIFIC named people (e.g. "John Smith at Stripe"). - **search-companies**: Find LISTS of companies. - **query-objects** + **ask-question-about-accounts**: the user's OWN accounts/deals/CRM. - **Follow-ups**: ALWAYS re-call this tool with an updated query — never filter results in chat. ## Parameters ### companyIdentifiers (required) One or more company domains or LinkedIn company URLs (up to 10). These companies are applied as a current-employer filter by the backend. Do NOT include `clay.filter_to_companies(...)` in dslQuery. ### dslQuery (required) A Search DSL query that MUST start with `select from people`. Include the requested person, role, seniority, location, and tenure filters; companyIdentifiers are attached separately by the backend. ## Search DSL Write a single Search DSL query. Grammar: ``` query = "select" "from" entity where? limit_by? limit? entity = "people" | "companies" where = "where" predicate limit_by = "limit" POSITIVE_INT "by" "clay_company_id" (people only) limit = "limit" INTEGER predicate = or_expr or_expr = and_expr ("or" and_expr)* and_expr = unary ("and" unary)* unary = "not" unary | comparison | aggregate | "(" predicate ")" comparison = field op value | field "is_null" | field "is_not_null" op = "=" | "!=" | "<" | "<=" | ">" | ">=" | "contains" | "starts_with" | "ends_with" | "in" | "not_in" | "is_similar_to" value = STRING | NUMBER | BOOLEAN | "(" value ("," value)* ")" | date_expr date_expr = "today" "(" ")" (("+" | "-") "interval" POSITIVE_INT unit)? unit = "day[s]" | "week[s]" | "month[s]" | "year[s]" ``` ### Operators - `contains` is whole-token match (not substring); list form: `field contains ("a", "b")`. - `in` / `not_in` take a value list; enum fields support only `=`, `!=`, `in`, `not_in`. - `is_similar_to` expands meaning (e.g. `job_title is_similar_to ("VP Sales")`). - `and` binds tighter than `or`; group with parentheses. ### Limits - Add `limit N` only when the user asks for a specific total count. - `limit N by clay_company_id` (people queries only) caps results per company. ### Company-scoped searches - Pass every requested current employer through companyIdentifiers. - Add role/seniority/tenure with `experiences.any(is_current = true and ...)`. - For a per-company cap ("N per company"), add `limit N by clay_company_id`. - Filtering people by their employer's ATTRIBUTES (industry, size, funding) uses `company.*` inside experiences.any(...) — this is an advanced cross-entity filter and may require a paid plan. ### People fields (top-level in `select from people`) - full_name (string): Full name of the person (first and last). - location_city (string): City name, e.g. 'San Francisco', 'Berlin'. Common: "Aberdeen", "Abilene", "Akron", "Albany", "Albuquerque", "Alexandria", "Allentown", "Amarillo", "Anaheim", "Anchorage", "Ann Arbor", "Antioch", "Apple Valley", "Appleton", "Arlington", "Arvada", "Asheville", "Atlanta", "Atlantic City", "Augusta", … - location_state (string): State, province, or municipality, e.g. 'California', 'Ontario'. - location_country (string, enum): Full country name, e.g. 'United States', 'Germany'. Values: "Afghanistan", "Åland Islands", "Albania", "Algeria", "American Samoa", "Andorra", "Angola", "Anguilla", "Antarctica", "Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Australia", "Austria", "Azerbaijan", "Bahamas", "Bahrain", "Bangladesh", "Barbados", "Belarus", "Belgium", "Belize", "Benin", "Bermuda", "Bhutan", "Bolivia", "Bosnia and Herzegovina", "Botswana", "Bouvet Island", "Brazil", "British Indian Ocean Territory", "Brunei Darussalam", "Bulgaria", "Burkina Faso", "Burundi", "Cambodia", "Cameroon", "Canada", "Cape Verde", "Cayman Islands", "Central African Republic", "Chad", "Chile", "China", "Christmas Island", "Cocos (Keeling) Islands", "Collectivity of Saint Martin", "Colombia", "Comoros", "Cook Islands", "Costa Rica", "Côte d'Ivoire", "Croatia", "Cuba", "Curaçao", "Cyprus", "Czech Republic", "Democratic Republic of the Congo", "Denmark", "Djibouti", "Dominica", "Dominican Republic", "Ecuador", "Egypt", "El Salvador", "Equatorial Guinea", "Eritrea", "Estonia", "Ethiopia", "Falkland Islands (Malvinas)", "Faroe Islands", "Fiji", "Finland", "France", "French Guiana", "French Polynesia", "French Southern Territories", "Gabon", "Gambia", "Georgia", "Germany", "Ghana", "Gibralta", "Greece", "Greenland", "Grenada", "Guadeloupe", "Guam", "Guatemala", "Guernsey", "Guinea-Bissau", "Guinea", "Guyana", "Haiti", "Heard Island and McDonald Islands", "Holy See", "Honduras", "Hong Kong", "Hungary", "Iceland", "India", "Indonesia", "Iran", "Iraq", "Ireland", "Isle of Man", "Israel", "Italy", "Jamaica", "Japan", "Jersey", "Jordan", "Kazakhstan", "Kenya", "Kiribati", "Kuwait", "Kyrgyzstan", "Laos", "Latvia", "Lebanon", "Lesotho", "Liberia", "Libya", "Liechtenstein", "Lithuania", "Luxembourg", "Macao", "Madagascar", "Malawi", "Malaysia", "Maldives", "Mali", "Malta", "Marshall Islands", "Martinique", "Mauritania", "Mauritius", "Mayotte", "Mexico", "Micronesia", "Moldova", "Monaco", "Mongolia", "Montenegro", "Montserrat", "Morocco", "Mozambique", "Myanmar", "Namibia", "Nauru", "Nepal", "Netherlands", "New Caledonia", "New Zealand", "Nicaragua", "Niger", "Nigeria", "Niue", "Norfolk Island", "North Korea", "North Macedonia", "Northern Mariana Islands", "Norway", "Oman", "Pakistan", "Palau", "Palestine", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines", "Pitcairn", "Poland", "Portugal", "Puerto Rico", "Qatar", "Republic of the Congo", "Réunion", "Romania", "Russia", "Rwanda", "Saint Barthélemy", "Saint Helena, Ascension and Tristan da Cunha", "Saint Kitts and Nevis", "Saint Lucia", "Saint Pierre and Miquelon", "Saint Vincent and the Grenadines", "Samoa", "San Marino", "Sao Tome and Principe", "Saudi Arabia", "Senegal", "Serbia", "Seychelles", "Sierra Leone", "Singapore", "Sint Maarten", "Slovakia", "Slovenia", "Solomon Islands", "Somalia", "South Africa", "South Georgia and the South Sandwich Islands", "South Korea", "South Sudan", "Spain", "Sri Lanka", "Sudan", "Suriname", "Swaziland", "Sweden", "Switzerland", "Syria", "Taiwan", "Tajikistan", "Tanzania", "Thailand", "Timor-Leste", "Togo", "Tokelau", "Tonga", "Trinidad and Tobago", "Tunisia", "Turkey", "Turkmenistan", "Turks and Caicos Islands", "Tuvalu", "Uganda", "Ukraine", "United Arab Emirates", "United Kingdom", "United States Minor Outlying Islands", "United States", "Uruguay", "Uzbekistan", "Vanuatu", "Venezuela", "Vietnam", "Virgin Islands, British", "Virgin Islands, U.S.", "Wallis and Futuna", "Western Sahara", "Yemen", "Zambia", "Zimbabwe" - location_region (string, enum): Geographic region. Values: "APAC", "EMEA", "LATAM", "NAM" - estimated_follower_count (number): Estimated social media audience/follower count. - network_size (number): Estimated professional network size (connection count). - years_of_experience (number): Estimated full-time years of experience based on full-time roles on the profile. - headline (string): Profile headline (the tagline below their name). Use contains for keyword matching. - about (string): About/summary section of the profile. Use contains for keyword matching. - languages (string, array): Languages listed on the profile. Use = for exact match, in for multiple. e.g. languages = "Spanish" or languages in ("Spanish", "French"). Common: "English", "Spanish", "French", "German", "Portuguese", "Chinese", "Japanese", "Hindi", "Arabic", "Korean", "Italian", "Dutch", "Russian" - education (tuple array): Education history. Use .any() or .count() with inner predicates on subfields. Subfields: - school_name (string): Name of the school or university. - degree (string): Degree obtained, e.g. 'Bachelor of Science', 'Master of Business Administration', 'PhD'. - field_of_study (string): Academic major or field, e.g. 'Computer Science', 'Economics', 'Mechanical Engineering'. - start_date (month): Date education started (YYYY-MM). - end_date (month): Date education ended (YYYY-MM). - description (string): Education description text. Use contains for keyword matching. - activities_and_societies (string): Activities and societies during education. Use contains for keyword matching. ### Experience fields (inside `experiences.any(...)`) - job_title (string): Job title of the experience. Common: "Academic Counselor", "Accountant", "Account Executive", "Accounting Analyst", "Accounting Clerk", "Accounting Manager", "Accounting Partner", "Accounting Supervisor", "Account Manager", "Account Representative", "Accounts Payable Clerk", "Accounts Payable Manager", "Accounts Receivable Clerk", "Accounts Receivable Manager", "Account Supervisor", "Activities Director", "Activities Worker", "Actor", "Actuary", "Acupuncturist", … - description (string): Experience description text. Use contains for keyword matching. - company_name (string): Company name for the experience. - employment_type (string): Type of employment. Common: "Full-time", "Part-time", "Internship", "Self-employed", "Contract", "Permanent", "Freelance", "Volunteer", "Other", "Temporary", "Apprenticeship" - seniority (string, enum): Seniority level of the role. Values: "Founder", "Owner", "Board Member" (Board member), "Partner", "C-suite", "VP", "Director", "Head", "Manager", "Senior", "Mid-level", "Entry", "Intern / In Training" (Intern / in training), "Unknown" - is_current (boolean): True if this is the person's current role, false for past roles. In `experiences.any(...)` on people queries, omit `is_current` to match any tenure. In `people.exists(...)` / `people.count(...)` on companies queries, include `is_current = true` by default when the user doesn't specify between current vs past. - start_date (month): Date the experience started (YYYY-MM). - end_date (month): Date the experience ended (YYYY-MM). Empty if current role. - location (string): Free-text location of the experience. - location_city (string): City of the experience, e.g. 'San Francisco'. Common: "Aberdeen", "Abilene", "Akron", "Albany", "Albuquerque", "Alexandria", "Allentown", "Amarillo", "Anaheim", "Anchorage", "Ann Arbor", "Antioch", "Apple Valley", "Appleton", "Arlington", "Arvada", "Asheville", "Atlanta", "Atlantic City", "Augusta", … - location_state (string): State or province of the experience, e.g. 'California'. - location_country (string, enum): Country of the experience, e.g. 'United States'. Values: "Afghanistan", "Åland Islands", "Albania", "Algeria", "American Samoa", "Andorra", "Angola", "Anguilla", "Antarctica", "Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Australia", "Austria", "Azerbaijan", "Bahamas", "Bahrain", "Bangladesh", "Barbados", "Belarus", "Belgium", "Belize", "Benin", "Bermuda", "Bhutan", "Bolivia", "Bosnia and Herzegovina", "Botswana", "Bouvet Island", "Brazil", "British Indian Ocean Territory", "Brunei Darussalam", "Bulgaria", "Burkina Faso", "Burundi", "Cambodia", "Cameroon", "Canada", "Cape Verde", "Cayman Islands", "Central African Republic", "Chad", "Chile", "China", "Christmas Island", "Cocos (Keeling) Islands", "Collectivity of Saint Martin", "Colombia", "Comoros", "Cook Islands", "Costa Rica", "Côte d'Ivoire", "Croatia", "Cuba", "Curaçao", "Cyprus", "Czech Republic", "Democratic Republic of the Congo", "Denmark", "Djibouti", "Dominica", "Dominican Republic", "Ecuador", "Egypt", "El Salvador", "Equatorial Guinea", "Eritrea", "Estonia", "Ethiopia", "Falkland Islands (Malvinas)", "Faroe Islands", "Fiji", "Finland", "France", "French Guiana", "French Polynesia", "French Southern Territories", "Gabon", "Gambia", "Georgia", "Germany", "Ghana", "Gibralta", "Greece", "Greenland", "Grenada", "Guadeloupe", "Guam", "Guatemala", "Guernsey", "Guinea-Bissau", "Guinea", "Guyana", "Haiti", "Heard Island and McDonald Islands", "Holy See", "Honduras", "Hong Kong", "Hungary", "Iceland", "India", "Indonesia", "Iran", "Iraq", "Ireland", "Isle of Man", "Israel", "Italy", "Jamaica", "Japan", "Jersey", "Jordan", "Kazakhstan", "Kenya", "Kiribati", "Kuwait", "Kyrgyzstan", "Laos", "Latvia", "Lebanon", "Lesotho", "Liberia", "Libya", "Liechtenstein", "Lithuania", "Luxembourg", "Macao", "Madagascar", "Malawi", "Malaysia", "Maldives", "Mali", "Malta", "Marshall Islands", "Martinique", "Mauritania", "Mauritius", "Mayotte", "Mexico", "Micronesia", "Moldova", "Monaco", "Mongolia", "Montenegro", "Montserrat", "Morocco", "Mozambique", "Myanmar", "Namibia", "Nauru", "Nepal", "Netherlands", "New Caledonia", "New Zealand", "Nicaragua", "Niger", "Nigeria", "Niue", "Norfolk Island", "North Korea", "North Macedonia", "Northern Mariana Islands", "Norway", "Oman", "Pakistan", "Palau", "Palestine", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines", "Pitcairn", "Poland", "Portugal", "Puerto Rico", "Qatar", "Republic of the Congo", "Réunion", "Romania", "Russia", "Rwanda", "Saint Barthélemy", "Saint Helena, Ascension and Tristan da Cunha", "Saint Kitts and Nevis", "Saint Lucia", "Saint Pierre and Miquelon", "Saint Vincent and the Grenadines", "Samoa", "San Marino", "Sao Tome and Principe", "Saudi Arabia", "Senegal", "Serbia", "Seychelles", "Sierra Leone", "Singapore", "Sint Maarten", "Slovakia", "Slovenia", "Solomon Islands", "Somalia", "South Africa", "South Georgia and the South Sandwich Islands", "South Korea", "South Sudan", "Spain", "Sri Lanka", "Sudan", "Suriname", "Swaziland", "Sweden", "Switzerland", "Syria", "Taiwan", "Tajikistan", "Tanzania", "Thailand", "Timor-Leste", "Togo", "Tokelau", "Tonga", "Trinidad and Tobago", "Tunisia", "Turkey", "Turkmenistan", "Turks and Caicos Islands", "Tuvalu", "Uganda", "Ukraine", "United Arab Emirates", "United Kingdom", "United States Minor Outlying Islands", "United States", "Uruguay", "Uzbekistan", "Vanuatu", "Venezuela", "Vietnam", "Virgin Islands, British", "Virgin Islands, U.S.", "Wallis and Futuna", "Western Sahara", "Yemen", "Zambia", "Zimbabwe" - location_region (string, enum): Geographic region of the experience. Values: "APAC", "EMEA", "LATAM", "NAM" ### Employer fields (inside `experiences.any(... company.* ...)`) - domain (string): Company website domain, e.g. 'google.com', 'stripe.com'. - description (string): Company description. Use contains for keyword matching. - products_and_services (string): What the company does, makes, and sells, matched semantically against company document embeddings. Only supports is_similar_to with one or more non-empty string values; multiple values match companies similar to ANY value (e.g. products_and_services is_similar_to ("b2b saas", "crm")). Distinct from description keyword matching; not all companies have embeddings, and rows without one never match. - company_type (string, enum): Company type classification. Values: "Privately Held" (Privately held), "Public Company" (Public company), "Partnership", "Self Employed" (Self-employed), "Non Profit" (Nonprofit), "Educational", "Self Owned" (Self-owned), "Government Agency" (Government agency) - company_size (string, enum): Company size range bucket. Prefer this for first-pass company-size filtering; use estimated_employee_count only when the user explicitly asks for exact employee count/headcount. Values: "1" (1 employee), "2-10" (2–10 employees), "11-50" (11–50 employees), "51-200" (51–200 employees), "201-500" (201–500 employees), "501-1,000" (501–1,000 employees), "1,001-5,000" (1,001–5,000 employees), "5,001-10,000" (5,001–10,000 employees), "10,001+" (10,001+ employees) - estimated_employee_count (number): Estimated total employee count. Use only when the user explicitly asks for exact employee count/headcount or asks to switch from company-size buckets to exact counts. - estimated_follower_count (number): Estimated social media audience/follower count. - year_founded (year): Year the company was founded. - employee_growth_3mo (number): Employee growth ratio (1.1 = +10% growth, 0.9 = −10% decline). - employee_growth_6mo (number): Employee growth ratio (1.1 = +10% growth, 0.9 = −10% decline). - employee_growth_12mo (number): Employee growth ratio (1.1 = +10% growth, 0.9 = −10% decline). - employee_growth_24mo (number): Employee growth ratio (1.1 = +10% growth, 0.9 = −10% decline). - annual_revenue (string, enum): Annual revenue bracket. Use = or in with exact bucket values, not numeric operators. Values: "0-500K" ($0–$500K), "500K-1M" ($500K–$1M), "1M-5M" ($1M–$5M), "5M-10M" ($5M–$10M), "10M-25M" ($10M–$25M), "25M-75M" ($25M–$75M), "75M-200M" ($75M–$200M), "200M-500M" ($200M–$500M), "500M-1B" ($500M–$1B), "1B-10B" ($1B–$10B), "10B-100B" ($10B–$100B), "100B-1T" ($100B+) - ai_business_types (string): Derived business model type. LOW COVERAGE — treat as optional: always pair with an is_null fallback, e.g. (ai_business_types contains "B2B" or ai_business_types is_null). Use contains for matching. Common: "B2B", "B2C", "Nonprofit" - industry (string, enum): The company's main industry. This is the primary, structured way to filter companies by industry. Values: "Abrasives and Nonmetallic Minerals Manufacturing", "Accessible Architecture and Design", "Accommodation Services", "Accounting", "Administration of Justice", "Administrative and Support Services", "Advertising Services", "Agricultural Chemical Manufacturing", "Agriculture, Construction, Mining Machinery Manufacturing", "Air, Water, and Waste Program Management", "Airlines and Aviation", "Alternative Dispute Resolution", "Alternative Medicine", "Ambulance Services", "Amusement Parks and Arcades", "Animal Feed Manufacturing", "Animation", "Animation and Post-production", "Apparel Manufacturing", "Apparel and Fashion", "Appliances, Electrical, and Electronics Manufacturing", "Architectural and Structural Metal Manufacturing", "Architecture and Planning", "Armed Forces", "Artists and Writers", "Arts and Crafts", "Audio and Video Equipment Manufacturing", "Automation Machinery Manufacturing", "Automotive", "Aviation & Aerospace", "Aviation and Aerospace Component Manufacturing", "Baked Goods Manufacturing", "Banking", "Bars, Taverns, and Nightclubs", "Bed-and-Breakfasts, Hostels, Homestays", "Beverage Manufacturing", "Biomass Electric Power Generation", "Biotechnology", "Biotechnology Research", "Blockchain Services", "Blogs", "Boilers, Tanks, and Shipping Container Manufacturing", "Book Publishing", "Book and Periodical Publishing", "Breweries", "Broadcast Media Production and Distribution", "Building Construction", "Building Equipment Contractors", "Building Finishing Contractors", "Building Materials", "Building Structure and Exterior Contractors", "Business Consulting and Services", "Business Content", "Business Intelligence Platforms", "Business Supplies and Equipment", "Capital Markets", "Caterers", "Chemical Manufacturing", "Chemical Raw Materials Manufacturing", "Child Day Care Services", "Chiropractors", "Civic and Social Organizations", "Civil Engineering", "Claims Adjusting, Actuarial Services", "Clay and Refractory Products Manufacturing", "Climate Data and Analytics", "Climate Technology Product Manufacturing", "Coal Mining", "Collection Agencies", "Commercial Real Estate", "Commercial and Industrial Equipment Rental", "Commercial and Industrial Machinery Maintenance", "Commercial and Service Industry Machinery Manufacturing", "Communications Equipment Manufacturing", "Community Development and Urban Planning", "Community Services", "Computer Games", "Computer Hardware", "Computer Hardware Manufacturing", "Computer Networking", "Computer Networking Products", "Computer and Network Security", "Computers and Electronics Manufacturing", "Conservation Programs", "Construction", "Construction Hardware Manufacturing", "Consumer Electronics", "Consumer Goods", "Consumer Goods Rental", "Consumer Services", "Cosmetics", "Cosmetology and Barber Schools", "Courts of Law", "Credit Intermediation", "Dairy", "Dairy Product Manufacturing", "Dance Companies", "Data Infrastructure and Analytics", "Data Security Software Products", "Defense & Space", "Defense and Space Manufacturing", "Dentists", "Design", "Design Services", "Desktop Computing Software Products", "Digital Accessibility Services", "Distilleries", "E-Learning", "E-Learning Providers", "Economic Programs", "Education", "Education Administration Programs", "Education Management", "Electric Lighting Equipment Manufacturing", "Electric Power Generation", "Electric Power Transmission, Control, and Distribution", "Electrical Equipment Manufacturing", "Electronic and Precision Equipment Maintenance", "Embedded Software Products", "Emergency and Relief Services", "Engineering Services", "Engines and Power Transmission Equipment Manufacturing", "Entertainment", "Entertainment Providers", "Environmental Quality Programs", "Environmental Services", "Equipment Rental Services", "Events Services", "Executive Offices", "Executive Search Services", "Fabricated Metal Products", "Facilities Services", "Farming, Ranching, Forestry", "Farming", "Fashion Accessories Manufacturing", "Financial Services", "Fine Art", "Fine Arts Schools", "Fire Protection", "Fisheries", "Flight Training", "Food & Beverages", "Food and Beverage Manufacturing", "Food and Beverage Retail", "Food and Beverage Services", "Food Production", "Footwear Manufacturing", "Forestry and Logging", "Freight and Package Transportation", "Fruit and Vegetable Preserves Manufacturing", "Fundraising", "Funds and Trusts", "Furniture", "Furniture and Home Furnishings Manufacturing", "Gambling Facilities and Casinos", "Geothermal Electric Power Generation", "Glass Product Manufacturing", "Glass, Ceramics and Concrete Manufacturing", "Golf Courses and Country Clubs", "Government Administration", "Government Relations", "Government Relations Services", "Graphic Design", "Ground Passenger Transportation", "HVAC and Refrigeration Equipment Manufacturing", "Health and Human Services", "Health, Wellness and Fitness", "Higher Education", "Highway, Street, and Bridge Construction", "Historical Sites", "Holding Companies", "Home Health Care Services", "Horticulture", "Hospitality", "Hospitals", "Hospitals and Health Care", "Hotels and Motels", "Household Appliance Manufacturing", "Household Services", "Household and Institutional Furniture Manufacturing", "Housing Programs", "Housing and Community Development", "Human Resources", "Human Resources Services", "Hydroelectric Power Generation", "IT Services and IT Consulting", "IT System Custom Software Development", "IT System Data Services", "IT System Design Services", "IT System Installation and Disposal", "IT System Operations and Maintenance", "IT System Testing and Evaluation", "IT System Training and Support", "Import and Export", "Individual and Family Services", "Industrial Automation", "Industrial Machinery Manufacturing", "Industry Associations", "Information Services", "Information Technology and Services", "Insurance", "Insurance Agencies and Brokerages", "Insurance Carriers", "Insurance and Employee Benefit Funds", "Interior Design", "International Affairs", "International Trade and Development", "Internet Marketplace Platforms", "Internet News", "Internet Publishing", "Investment Advice", "Investment Banking", "Investment Management", "Janitorial Services", "Landscaping Services", "Language Schools", "Laundry and Drycleaning Services", "Law Enforcement", "Law Practice", "Leasing Non-residential Real Estate", "Leasing Residential Real Estate", "Leather Product Manufacturing", "Legal Services", "Legislative Offices", "Leisure, Travel & Tourism", "Libraries", "Loan Brokers", "Luxury Goods and Jewelry", "Machinery Manufacturing", "Manufacturing", "Maritime", "Maritime Transportation", "Market Research", "Marketing Services", "Mattress and Blinds Manufacturing", "Measuring and Control Instrument Manufacturing", "Meat Products Manufacturing", "Mechanical or Industrial Engineering", "Media & Telecommunications", "Media Production", "Medical Devices", "Medical Equipment Manufacturing", "Medical Practices", "Medical and Diagnostic Laboratories", "Mental Health Care", "Metal Ore Mining", "Metal Treatments", "Metal Valve, Ball, and Roller Manufacturing", "Metalworking Machinery Manufacturing", "Military and International Affairs", "Mining", "Mobile Computing Software Products", "Mobile Food Services", "Mobile Gaming Apps", "Motor Vehicle Manufacturing", "Motor Vehicle Parts Manufacturing", "Movies and Sound Recording", "Movies, Videos and Sound", "Museums", "Museums, Historical Sites, and Zoos", "Music", "Musicians", "Nanotechnology Research", "Natural Gas Distribution", "Newspaper Publishing", "Non-profit Organization Management", "Non-profit Organizations", "Nonmetallic Mineral Mining", "Nonresidential Building Construction", "Nuclear Electric Power Generation", "Nursing Homes and Residential Care Facilities", "Office Administration", "Office Furniture and Fixtures Manufacturing", "Oil and Gas", "Oil, Gas, and Mining", "Online Audio and Video Media", "Online Media", "Online and Mail Order Retail", "Operations Consulting", "Optometrists", "Outpatient Care Centers", "Outsourcing and Offshoring Consulting", "Outsourcing/Offshoring", "Packaging and Containers", "Packaging and Containers Manufacturing", "Paint, Coating, and Adhesive Manufacturing", "Paper and Forest Product Manufacturing", "Paper and Forest Products", "Performing Arts", "Performing Arts and Spectator Sports", "Periodical Publishing", "Personal Care Product Manufacturing", "Personal Care Services", "Personal and Laundry Services", "Pet Services", "Pharmaceutical Manufacturing", "Philanthropic Fundraising Services", "Philanthropy", "Photography", "Physical, Occupational and Speech Therapists", "Physicians", "Plastics Manufacturing", "Plastics and Rubber Product Manufacturing", "Political Organizations", "Primary Metal Manufacturing", "Primary and Secondary Education", "Printing Services", "Professional Organizations", "Professional Services", "Professional Training and Coaching", "Program Development", "Public Assistance Programs", "Public Health", "Public Policy", "Public Policy Offices", "Public Relations and Communications Services", "Public Safety", "Radio and Television Broadcasting", "Rail Transportation", "Railroad Equipment Manufacturing", "Ranching", "Real Estate", "Real Estate Agents and Brokers", "Real Estate and Equipment Rental Services", "Recreational Facilities", "Religious Institutions", "Renewable Energy Equipment Manufacturing", "Renewable Energy Power Generation", "Renewable Energy Semiconductor Manufacturing", "Renewables & Environment", "Repair and Maintenance", "Research", "Research Services", "Residential Building Construction", "Restaurants", "Retail", "Retail Apparel and Fashion", "Retail Appliances, Electrical, and Electronic Equipment", "Retail Art Dealers", "Retail Art Supplies", "Retail Books and Printed News", "Retail Building Materials and Garden Equipment", "Retail Florists", "Retail Furniture and Home Furnishings", "Retail Gasoline", "Retail Groceries", "Retail Health and Personal Care Products", "Retail Luxury Goods and Jewelry", "Retail Motor Vehicles", "Retail Musical Instruments", "Retail Office Equipment", "Retail Office Supplies and Gifts", "Retail Pharmacies", "Retail Recyclable Materials & Used Merchandise", "Reupholstery and Furniture Repair", "Robotics Engineering", "Rubber Products Manufacturing", "Satellite Telecommunications", "School and Employee Bus Services", "Seafood Product Manufacturing", "Securities and Commodity Exchanges", "Security Guards and Patrol Services", "Security Systems Services", "Security and Investigations", "Semiconductor Manufacturing", "Semiconductors", "Services for Renewable Energy", "Services for the Elderly and Disabled", "Sheet Music Publishing", "Shipbuilding", "Shuttles and Special Needs Transportation Services", "Sightseeing Transportation", "Soap and Cleaning Product Manufacturing", "Social Networking Platforms", "Software Development", "Solar Electric Power Generation", "Sound Recording", "Space Research and Technology", "Specialty Trade Contractors", "Spectator Sports", "Sporting Goods", "Sporting Goods Manufacturing", "Sports Teams and Clubs", "Sports and Recreation Instruction", "Spring and Wire Product Manufacturing", "Staffing and Recruiting", "Steam and Air-Conditioning Supply", "Strategic Management Services", "Subdivision of Land", "Sugar and Confectionery Product Manufacturing", "Surveying and Mapping Services", "Taxi and Limousine Services", "Technical and Vocational Training", "Technology, Information and Internet", "Technology, Information and Media", "Telecommunications", "Telecommunications Carriers", "Telephone Call Centers", "Temporary Help Services", "Textile Manufacturing", "Theater Companies", "Think Tanks", "Tobacco", "Tobacco Manufacturing", "Translation and Localization", "Transportation Equipment Manufacturing", "Transportation Programs", "Transportation, Logistics, Supply Chain and Storage", "Transportation/Trucking/Railroad", "Travel Arrangements", "Truck Transportation", "Trusts and Estates", "Turned Products and Fastener Manufacturing", "Urban Transit Services", "Utilities", "Utilities Administration", "Utility System Construction", "Vehicle Repair and Maintenance", "Venture Capital and Private Equity Principals", "Veterinary", "Veterinary Services", "Vocational Rehabilitation Services", "Warehousing", "Warehousing and Storage", "Waste Collection", "Waste Treatment and Disposal", "Water Supply and Irrigation Systems", "Water, Waste, Steam, and Air Conditioning Services", "Wellness and Fitness Services", "Wholesale", "Wholesale Alcoholic Beverages", "Wholesale Apparel and Sewing Supplies", "Wholesale Appliances, Electrical, and Electronics", "Wholesale Building Materials", "Wholesale Chemical and Allied Products", "Wholesale Computer Equipment", "Wholesale Drugs and Sundries", "Wholesale Food and Beverage", "Wholesale Footwear", "Wholesale Furniture and Home Furnishings", "Wholesale Hardware, Plumbing, Heating Equipment", "Wholesale Import and Export", "Wholesale Luxury Goods and Jewelry", "Wholesale Machinery", "Wholesale Metals and Minerals", "Wholesale Motor Vehicles and Parts", "Wholesale Paper Products", "Wholesale Petroleum and Petroleum Products", "Wholesale Raw Farm Products", "Wholesale Recyclable Materials", "Wind Electric Power Generation", "Wine and Spirits", "Wineries", "Wireless Services", "Wood Product Manufacturing", "Writing and Editing", "Zoos and Botanical Gardens" - naics_codes_2022 (string, enum, array): NAICS 2022 industry classification codes as numeric strings (2-6 digits). Matching is hierarchical: a code matches companies whose more specific codes fall under it (e.g. "5132" matches a company classified "513210"). Census publishes three 2-digit sectors as ranges: "31-33" (Manufacturing), "44-45" (Retail Trade), "48-49" (Transportation and Warehousing). Use = for one code, in for multiple, e.g. naics_codes_2022 in ("31-33", "541511"). Values: "11" (11: Agriculture, Forestry, Fishing and Hunting), "111" (111: Crop Production), "1111" (1111: Oilseed and Grain Farming), "11111" (11111: Soybean Farming), "111110" (111110: Soybean Farming), "11112" (11112: Oilseed (except Soybean) Farming), "111120" (111120: Oilseed (except Soybean) Farming), "11113" (11113: Dry Pea and Bean Farming), "111130" (111130: Dry Pea and Bean Farming), "11114" (11114: Wheat Farming), "111140" (111140: Wheat Farming), "11115" (11115: Corn Farming), "111150" (111150: Corn Farming), "11116" (11116: Rice Farming), "111160" (111160: Rice Farming), "11119" (11119: Other Grain Farming), "111191" (111191: Oilseed and Grain Combination Farming), "111199" (111199: All Other Grain Farming), "1112" (1112: Vegetable and Melon Farming), "11121" (11121: Vegetable and Melon Farming), … - ai_industries (string, enum, array): AI-derived industry classification. Do NOT filter on this field unless the user explicitly asks for ai_industries — default vertical filtering uses industry. Use = for exact match, in for multiple. e.g. ai_industries = "Professional, Business and Legal Services". Values: "Agriculture, Forestry and Fisheries", "Automotive, Aerospace and Defense Manufacturing", "Education and Training", "Energy, Utilities and Environmental Services", "Finance and Insurance", "Healthcare and Life Sciences", "Hospitality, Food and Travel Services", "Industrial Manufacturing and Materials", "Media, Entertainment and Culture", "Non-Profit, Public Sector and Education (Non-Commercial)", "Personal and Home Services", "Professional, Business and Legal Services", "Real Estate and Construction", "Retail and Consumer Channels", "Software and IT", "Transportation and Logistics" - ai_subindustries (string, enum, array): AI-derived subindustry classification. Use = for exact match, in for multiple. e.g. ai_subindustries = "AI and ML Platforms". Values: "AI and ML Platforms", "Agriculture and Forestry Software", "Blockchain and Web3", "Carriers and ISPs", "Cloud and Infrastructure Software", "Consumer Software", "Data and Analytics Software", "Developer Tools and Platforms", "Enterprise Software Solutions", "Financial Services Software", "Government and Public Sector Software", "Hardware and Networking", "Healthcare Software", "IoT and Embedded Systems Software", "IT Services and Cybersecurity", "Manufacturing Software", "Metaverse, AR/VR and Other Emerging Platforms", "Quantum Computing Software", "Real Estate and PropTech Software", "Retail and Ecommerce Software", "Security and Identity Software", "Biotechnology and Pharmaceuticals", "Digital Health and Telemedicine", "Hospitals, Clinics and Outpatient Care", "Medical Devices and Diagnostic Equipment", "Medical Testing and Clinical Laboratories", "Mental Health and Rehabilitation Services", "Pharma Distribution and CRO Services", "Banking and Lending", "Capital Markets and Cryptocurrency", "Cryptocurrency and Blockchain Services", "Financial Services Platforms", "Insurance and InsurTech", "Investment Management and WealthTech", "Venture Capital and Private Equity", "Electric Power and Grid Management", "Nuclear and Advanced Generation", "Oil and Gas Exploration, Production and Services", "Renewable Energy and Clean Tech", "Sustainability Tech and Environmental Consulting", "Water, Waste and Environmental Management", "3D Printing and Advanced Manufacturing", "Building Materials and Chemicals", "Consumer Goods and Appliances", "Electronics and Computer Equipment", "Food, Beverage and Tobacco Production", "Industrial Machinery and Equipment", "Mining, Metals and Natural Resources", "Architecture, Urban Planning and Green Building", "Commercial Real Estate Development and Leasing", "Construction and Civil Engineering Services", "Property and Facility Management", "Residential Real Estate Development and Brokerage", "Specialty Construction Products", "Automotive Service and Collision Repair", "Brick-and-Mortar Retail", "Media and Entertainment Retail", "Online Commerce and Marketplaces", "Retail Technology", "Specialty Auctions and Collectibles", "Wholesale and Distribution", "Autonomous Vehicles and Drone Delivery", "Car and Truck Rental", "Freight and Cargo", "Logistics Technology", "Passenger Transit and Mobility", "Warehousing, Fulfillment and 3PL Services", "Accounting, Audit and Financial Advisory", "Advertising, Marketing and Multimedia Design", "Defense and Government Services", "Facilities Management and Commercial Cleaning", "Human Resources, Staffing and Recruitment", "Legal Services and Regulatory Compliance", "Management Consulting and Strategy Consulting", "Translation, Document and Information Management", "Corporate Training and Learning and Development", "E-Learning Platforms and EdTech", "K-12 and Higher Education Institutions", "Test Prep, Tutoring and After-School Services", "Vocational Training and Certification Programs", "Digital Publishing and Streaming Platforms", "Film, Television and Broadcasting", "Gaming, Esports and Interactive Entertainment", "Live Events, Experiences and Ticketed Attractions", "Museums, Art Galleries and Cultural Preservation", "Music, Audio and Podcast Services", "Sports and Recreation", "Food and Beverage Services", "Hospitality and Lodging", "Travel Agencies and Leisure Services", "Funeral Homes and Related Services", "Home Services", "Personal Care and Wellness", "Veterinary Care and Pet Services", "AgriTech and Precision Farming", "Aquaculture and Fisheries", "Crop Farming and Livestock Production", "Farming Equipment and Supplies", "Forestry, Logging and Wood Products", "Mining and Extraction", "Aviation and Aerospace Component Manufacturing", "Automotive and Rental Retail", "Commercial Space Innovation", "Defense Systems and Marine Manufacturing", "Motor Vehicle and Parts Manufacturing", "Government Administration and Municipal Services", "NGOs, Charities and Community Organizations", "Public Healthcare and Social Services", "Public/Private Research Institutions and Educational Foundations", "Student Organizations and Campus Services" - ai_revenue_streams (string, enum, array): AI-derived revenue stream classification. Do NOT filter on this field unless the user explicitly asks for revenue streams. Use = for exact match, in for multiple. e.g. ai_revenue_streams = "SaaS". Values: "Professional Services", "Financial Services", "Subscriptions/Recurring", "Product Sales", "Transaction Fees", "Rental/Leasing", "Project/Contract Work", "Event/Experience Revenue", "Grants/Donations", "Licensing/IP", "Advertising" - locations (tuple array): All office locations. Use .any() or .count() with inner predicates on subfields. Subfields: - country_name (string, enum): Full country name, e.g. 'United States', 'Germany'. Values: "Afghanistan", "Albania", "Algeria", "Andorra", "Angola", "Anguilla", "Antarctica", "Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Australia", "Austria", "Azerbaijan", "Bahamas", "Bahrain", "Bangladesh", "Barbados", "Belarus", "Belgium", "Belize", "Benin", "Bermuda", "Bhutan", "Bolivia", "Bonaire, Saint Eustatius and Saba ", "Bosnia and Herzegovina", "Botswana", "Brazil", "British Virgin Islands", "Brunei", "Bulgaria", "Burkina Faso", "Burundi", "Cambodia", "Cameroon", "Canada", "Cape Verde", "Cayman Islands", "Central African Republic", "Chad", "Chile", "China", "Colombia", "Comoros", "Costa Rica", "Croatia", "Cuba", "Curacao", "Cyprus", "Czechia", "Democratic Republic of the Congo", "Denmark", "Djibouti", "Dominican Republic", "East Timor", "Ecuador", "Egypt", "El Salvador", "Equatorial Guinea", "Estonia", "Ethiopia", "Faroe Islands", "Fiji", "Finland", "France", "French Guiana", "French Polynesia", "Gabon", "Gambia", "Georgia", "Germany", "Ghana", "Gibraltar", "Greece", "Greenland", "Grenada", "Guadeloupe", "Guam", "Guatemala", "Guernsey", "Guinea", "Guyana", "Haiti", "Honduras", "Hong Kong", "Hungary", "Iceland", "India", "Indonesia", "Iran", "Iraq", "Ireland", "Isle of Man", "Israel", "Italy", "Ivory Coast", "Jamaica", "Japan", "Jersey", "Jordan", "Kazakhstan", "Kenya", "Kosovo", "Kuwait", "Kyrgyzstan", "Laos", "Latvia", "Lebanon", "Lesotho", "Liberia", "Libya", "Liechtenstein", "Lithuania", "Luxembourg", "Macao", "Macedonia", "Madagascar", "Malawi", "Malaysia", "Maldives", "Mali", "Malta", "Marshall Islands", "Martinique", "Mauritania", "Mauritius", "Mayotte", "Mexico", "Moldova", "Monaco", "Mongolia", "Montenegro", "Morocco", "Mozambique", "Myanmar", "Namibia", "Nepal", "Netherlands", "Netherlands Antilles", "New Caledonia", "New Zealand", "Nicaragua", "Niger", "Nigeria", "North Korea", "Northern Mariana Islands", "Norway", "Oman", "Pakistan", "Palestinian Territory", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines", "Poland", "Portugal", "Puerto Rico", "Qatar", "Republic of the Congo", "Reunion", "Romania", "Russia", "Rwanda", "Saint Barthelemy", "Saint Kitts and Nevis", "Saint Lucia", "Saint Vincent and the Grenadines", "Samoa", "San Marino", "Sao Tome and Principe", "Saudi Arabia", "Senegal", "Serbia", "Serbia and Montenegro", "Seychelles", "Sierra Leone", "Singapore", "Sint Maarten", "Slovakia", "Slovenia", "Somalia", "South Africa", "South Korea", "South Sudan", "Spain", "Sri Lanka", "Sudan", "Suriname", "Svalbard and Jan Mayen", "Swaziland", "Sweden", "Switzerland", "Syria", "Taiwan", "Tajikistan", "Tanzania", "Thailand", "Togo", "Tonga", "Trinidad and Tobago", "Tunisia", "Turkey", "Turkmenistan", "Turks and Caicos Islands", "U.S. Virgin Islands", "Uganda", "Ukraine", "United Arab Emirates", "United Kingdom", "United States", "Uruguay", "Uzbekistan", "Vanuatu", "Venezuela", "Vietnam", "Yemen", "Zambia", "Zimbabwe" - city (string): City name, e.g. 'San Francisco', 'Berlin'. Common: "Aberdeen", "Abilene", "Akron", "Albany", "Albuquerque", "Alexandria", "Allentown", "Amarillo", "Anaheim", "Anchorage", "Ann Arbor", "Antioch", "Apple Valley", "Appleton", "Arlington", "Arvada", "Asheville", "Atlanta", "Atlantic City", "Augusta", … - state_or_province (string): State, province, or first-level administrative district, e.g. 'California', 'Ontario'. - postal_code (string): Postal or ZIP code, e.g. '94107'. - region (string, enum): Business region for the office location. Values: "APAC", "EMEA", "LATAM", "NAM" - is_headquarters (boolean): True when this location is the company headquarters (primary office). - technographics (tuple array): Technology stack installed at the company, backed by BuyerCaddy data. Use .any() or .count() with inner predicates on subfields. Subfields: - vendor (string): Technology vendor name. Common: "Microsoft", "Google", "Amazon", "Adobe", "Oracle", "The PHP Group", "Facebook, Inc.", "Automattic Inc.", "Cloudflare", "Apache", "Meta Platforms, Inc" - product (string): Product name. Common: "Amazon Web Services (AWS)", "Amazon Web Hosting", "Google Analytics 360", "PHP", "Google Tag Manager", "Microsoft 365 Apps & Services", "Google Marketing Platform", "Amazon EC2", "Microsoft Exchange", "GoDaddy Hosting" - product_category (string): Top-level product category. Common: "IT Infrastructure", "Collaboration & Productivity", "Marketing", "Development", "Content Management", "Digital Advertising Tech", "Hosting", "CI/CD Tools", "Cloud Data Integration", "Web Hosting" - product_subcategory (string): Most specific product category for an install, normally a child of product_category. The provider may supply one or two category levels; when it supplies one, the value lands here and product_category is empty. Populated more consistently than product_category. Common: "Operating System", "Cloud Infrastructure Automation", "iPaaS", "Collaboration & Productivity", "Digital Analytics", "Tag Management Systems", "Paid Search Advertising", "Office Suites", "Infrastructure as a Service (IaaS)", "Web Content Management" ## Examples | User says | companyIdentifiers | dslQuery | |-----------|--------------------|----------| | "engineers at Stripe" | `["stripe.com"]` | `select from people where experiences.any(is_current = true and job_title is_similar_to ("engineer"))` | | "up to 5 VPs of Sales at Stripe, Ramp, and Brex" | `["stripe.com", "ramp.com", "brex.com"]` | `select from people where experiences.any(is_current = true and job_title is_similar_to ("VP Sales")) limit 5 by clay_company_id` | | "new hires at Stripe in the last 3 months" | `["stripe.com"]` | `select from people where experiences.any(is_current = true and start_date >= today() - interval 3 months)` | ## Handling Follow-ups ANY change to the search requires re-calling this tool with a modified query — never filter in chat. - "also / too" → add predicates with `and`, keeping prior filters. - "only / just" → narrow the relevant predicate. - "instead / actually" → replace the relevant predicate. - When ambiguous, ask the user. ## Response Behavior - Summarize the search briefly (e.g., "Found 20 engineers at OpenAI"). - The tool returns a taskId for use with add-contact-data-points, add-company-data-points, custom functions, or get-task-context. - For emails, use add-contact-data-points with the taskId. Clay may render results in a widget in hosts that support MCP Apps, such as ChatGPT, claude.ai, and Cursor. Other terminal/coding-agent hosts such as Codex, Claude Code, Windsurf, and CLI environments do not show the widget. If you are unsure whether the widget is visible, assume it is not visible. - If a widget is visible, avoid repeating the full widget contents unless the user asks for full contents; then call get-task-context with the taskId and answer inline. - In terminal/coding-agent environments, when no widget is visible, or when the user asks for actual values/results, call get-task-context with the taskId and answer inline. - **NEVER tell the user that data was not found, not returned, or unavailable without first calling get-task-context.** The initial search/tool response only includes base fields — enrichment results (emails, X/Twitter profiles, work history, custom data points, etc.) are only available via get-task-context. - **When the user asks about a specific value** (e.g. "what's Patrick's email?", "what X profiles did you get?"), call get-task-context FIRST to check if the data has already been enriched — the user may have triggered enrichments through the widget. Only call add-contact-data-points / add-company-data-points if get-task-context shows the enrichment hasn't been run yet. - Use get-task-context to poll until async results complete; if values are still in-progress, wait and retry rather than answering with missing values. - If get-task-context is not available, fall back to get-task. ## Zero Results Suggest broadening: relax role terms (is_similar_to already expands), drop location or tenure, or verify the companyIdentifiers. ## Displaying Results This tool returns data only, and this client has no results widget. Present the results yourself, concisely — a compact list or table of the returned records with the fields the user cares about (e.g. name, title, company, LinkedIn URL). When the search reports `hasMore: true` and the user wants more, call `load-more-search-results` with the returned `taskId`. ## Enrichment This tool does NOT enrich (it takes no data points). To add emails, work history, funding, tech stack, custom research, etc., call `add-contact-data-points` (for contacts) or `add-company-data-points` (for companies) with the returned `taskId` after this tool.
The description explains the capability, when to use it, and what to expect.
Inputs75/100
Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.
companyIdentifiers
One or more company identifiers to search contacts at (up to 10). Each is a domain (e.g. "clay.com") or a LinkedIn company URL (e.g. "https://www.linkedin.com/company/grow-with-clay"). Pass multiple to run the same role/title filters across several companies at once.
Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.
dslQuery
A Search DSL query. Must start with `select from people`.
Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.
Annotations75/100
Declare idempotentHint based on the tool’s actual behavior.
{
"readOnlyHint": true,
"openWorldHint": false,
"destructiveHint": false
}Output schema0/100
No output schema is declared. Add one for structured results so clients can interpret returned fields.
Not declared