> ## Documentation Index > Fetch the complete documentation index at: https://aisa.one/docs/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > - Base URLs: models `https://api.aisa.one/v1` (Gemini GenerateContent: `https://api.aisa.one/v1beta`); data APIs `https://api.aisa.one/apis/v1`. The `servers` of each operation in https://aisa.one/openapi.yaml is authoritative. > - Auth: `Authorization: Bearer $AISA_API_KEY`. Never print, log, or commit the key. > - MCP (preferred for agents): `https://mcp.aisa.one/mcp`, signed in with OAuth, so there is no key to paste. > - Agent Skill: `npx skills add AIsa-team/agent-skills --skill aisa`. Fallback with the AIsa CLI: `aisa skills install aisa`. > - Spending: docs, https://aisa.one/models, https://aisa.one/api, `/v1/models`, and MCP `search`, `list_categories`, `get_details`, `batch_quote`, and the `account` operation are free. Quote the exact calls before running them (MCP `batch_quote`, CLI `aisa quote --json`). If the quote reports `auto_execute_eligible: true`, run it unless the user set a tighter limit or asked only for a quote. Otherwise, tell the user in one message the planned calls, the quoted price, and a total USD budget for the task, then wait for approval. Direct HTTP calls follow the stricter rule at https://aisa.one/docs/get-started/cli.md#direct-http-fallback. Do not make paid calls to test availability. Full rule: https://aisa.one/llms.txt # Enrich person data > 按用量计费；默认请求预估费用：$0.2803 USD（不是固定价格）。 声明的单位费率：每 provider_credit $0.000001 USD。 最终费用以账户适用价格及实际结算为准。 ## 请求规范 * **方法与路径:** POST /apis/v1/people-data-labs/enrich-person-data * **可用状态:** enabled * **请求 URL 模板:** `https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data` * **Runtime 事实版本:** d9aafd76ae02b9bcd98e168c52eb69aba6e12890a1eed8da421910f394e8200a [完整 OpenAPI 定义](https://aisa.one/docs/reference-contracts/zh/people-data-labs.json) 有效请求与价格声明（包括认证和引用的 schema）： ```json theme={null} { "operationId": "people-data-labs.enrich-person-data", "method": "POST", "path": "/apis/v1/people-data-labs/enrich-person-data", "servers": [ { "url": "https://api.aisa.one" } ], "parameters": [], "security": [ { "bearerAuth": [] } ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "lid": { "type": "string", "examples": [ "123456789" ], "description": "LinkedIn ID." }, "name": { "type": "string", "examples": [ "John Michael Doe" ], "description": "Full name." }, "email": { "type": "string", "description": "Email address.", "examples": [ "john.doe@example.com" ] }, "phone": { "type": "string", "examples": [ "+14155552671" ], "description": "Phone number; E.164 format recommended." }, "pdl_id": { "type": "string", "examples": [ "qEnxS5T1G2YvasA1x24qoA_0000" ], "description": "People Data Labs unique record ID." }, "pretty": { "type": "boolean", "default": true, "description": "Format JSON response with indentation for readability." }, "region": { "type": "string", "examples": [ "CA" ], "description": "State, province, or region of residence." }, "school": { "type": "string", "examples": [ "Stanford University" ], "description": "School name attended." }, "company": { "type": "string", "examples": [ "Acme Corporation" ], "description": "Company name where person has worked." }, "country": { "type": "string", "examples": [ "US", "United States" ], "description": "Country of residence (ISO 3166-1 alpha-2 code or full name)." }, "profile": { "type": "string", "examples": [ "https://www.linkedin.com/in/john-doe", "https://www.facebook.com/jane.doe" ], "description": "Social profile URL (e.g., LinkedIn, Facebook)." }, "locality": { "type": "string", "examples": [ "San Francisco" ], "description": "City or locality of residence." }, "location": { "type": "string", "examples": [ "San Francisco, CA, USA" ], "description": "General location (e.g., city, state, country)." }, "required": { "type": "string", "examples": [ "emails AND phone_numbers", "education AND (emails OR phone_numbers)", "job_title AND job_company_name", "experience AND work_email" ], "description": "Boolean expression of top-level fields required in enriched profile for match. Use AND/OR operators and parentheses for logic (e.g., 'emails AND phone_numbers', 'education AND (emails OR phone_numbers)'). Valid fields: emails, phone_numbers, experience, education, job_title, job_company_name, full_name, location_country, work_email, personal_emails, mobile_phone, linkedin_url, profiles, skills, etc." }, "last_name": { "type": "string", "examples": [ "Doe" ], "description": "Last name." }, "birth_date": { "type": "string", "examples": [ "1990-01-15" ], "description": "Birth date (YYYY-MM-DD format)." }, "email_hash": { "type": "string", "examples": [ "d41d8cd98f00b204e9800998ecf8427e", "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855" ], "description": "SHA-256 or MD5 hash of an email, for matching without exposing the raw email." }, "first_name": { "type": "string", "examples": [ "John" ], "description": "First name." }, "postal_code": { "type": "string", "examples": [ "94107" ], "description": "Postal or ZIP code of residence." }, "data_include": { "type": "string", "examples": [ "emails,phones,profiles", "jobs,education" ], "description": "Comma-separated data fields to include in response (e.g., 'emails,phones'). Refer to People Data Labs docs for all fields." }, "min_likelihood": { "type": "integer", "default": 2, "maximum": 10, "minimum": 0, "examples": [ 0, 5, 10 ], "description": "Minimum confidence score (0-10) for a match to be returned; higher is stricter." }, "street_address": { "type": "string", "examples": [ "123 Main St" ], "description": "Street address." }, "include_if_matched": { "type": "boolean", "default": false, "description": "Include input parameters used for matching in the response if true." } }, "required": [ "email" ] } } } }, "x-aisa-status": "enabled", "x-aisa-pricing": { "cost_contract": "response_units", "customer_multiplier": 1.0, "customer_pricing": "provider_cost_multiplier", "default_request_estimate_usd": 0.2803, "estimate_source": "profile_seed", "evidence_source": "response_body", "maximum_units": 10000000, "unit": "provider_credit", "unit_rate_usd": 1e-06 }, "components": { "securitySchemes": { "bearerAuth": { "scheme": "bearer", "type": "http" } } } } ``` ## 费用与请求规则 按用量计费；默认请求预估费用：\$0.2803 USD（不是固定价格）。 声明的单位费率：每 provider\_credit \$0.000001 USD。 最终费用以账户适用价格及实际结算为准。 公开参考值不是你的账户报价或最终扣费。对于支持 X-AISA-Cost-Mode: quote 的接口，执行前请针对完整请求获取免费报价；执行后通过响应费用元数据和 Usage Logs 核对结算费用。1 USD 等于 1,000,000 个整数 micro-USD。 * **默认请求参考估价（USD）:** 0.2803 * **声明的单位费率（USD）:** 1e-06 * **计费单位:** provider\_credit * **计费依据:** response\_units * **公开参考倍率:** 1.0 * **声明的最大计数或单位数:** 10000000 * **结算证据来源:** response\_body ## OpenAPI ````yaml reference-contracts/zh/people-data-labs.json POST /apis/v1/people-data-labs/enrich-person-data openapi: 3.1.0 info: description: '' title: People Data Labs version: '1' x-aisa-capabilities: idempotency: Idempotency-Key max_price: X-AISA-Max-Price-USD quote: header: X-AISA-Cost-Mode value: quote x-aisa-configured-paths: - /apis/v1/people-data-labs/companies-enrich - /apis/v1/people-data-labs/companies-search - /apis/v1/people-data-labs/company/enrich - /apis/v1/people-data-labs/company/search - /apis/v1/people-data-labs/enrich-bulk-company-data - /apis/v1/people-data-labs/enrich-bulk-person-data - /apis/v1/people-data-labs/enrich-company-data - /apis/v1/people-data-labs/enrich-person-data - /apis/v1/people-data-labs/identify-person-data - /apis/v1/people-data-labs/people-enrich - /apis/v1/people-data-labs/people-search - /apis/v1/people-data-labs/people-search-elastic - /apis/v1/people-data-labs/search-company-elastic - /apis/v1/people-data-labs/search-company-post x-aisa-document: facts_hash: d9aafd76ae02b9bcd98e168c52eb69aba6e12890a1eed8da421910f394e8200a generator_version: '3' protocol_version: '1' schema_version: '1' composer_version: '28' response_pending: - operation_id: people-data-labs.companies-enrich path: /apis/v1/people-data-labs/companies-enrich method: GET statuses: - '200' reason: public success response has no authoritative payload declaration - operation_id: people-data-labs.companies-search path: /apis/v1/people-data-labs/companies-search method: GET statuses: - '200' reason: public success response has no authoritative payload declaration - operation_id: people-data-labs.people-enrich path: /apis/v1/people-data-labs/people-enrich method: GET statuses: - '200' reason: public success response has no authoritative payload declaration - operation_id: people-data-labs.people-search path: /apis/v1/people-data-labs/people-search method: GET statuses: - '200' reason: public success response has no authoritative payload declaration document_hash: sha256:fcc357eea49c3a145e5ed0f836a0034070b32bf97d92453e0a56ff91d1d4e687 x-aisa-plans: builder: 1 display_plan: payg payg: 1 similarweb_payg: 1 team: 1 version: e70a0959cd1b93b84ae16dffd7a538273ddb9c1d46277b82823c37ff1b6bc0fb x-aisa-provider: people-data-labs x-aisa-catalogs: people-data-labs: title: People Data Labs description: '' x-aisa-document: facts_hash: d9aafd76ae02b9bcd98e168c52eb69aba6e12890a1eed8da421910f394e8200a generator_version: '3' protocol_version: '1' schema_version: '1' x-aisa-plans: builder: 1 display_plan: payg payg: 1 similarweb_payg: 1 team: 1 version: e70a0959cd1b93b84ae16dffd7a538273ddb9c1d46277b82823c37ff1b6bc0fb x-aisa-capabilities: idempotency: Idempotency-Key max_price: X-AISA-Max-Price-USD quote: header: X-AISA-Cost-Mode value: quote servers: - url: https://api.aisa.one security: - bearerAuth: [] paths: /apis/v1/people-data-labs/enrich-person-data: post: tags: - People Data Labs summary: Enrich person data description: >- 按用量计费；默认请求预估费用：$0.2803 USD（不是固定价格）。 声明的单位费率：每 provider_credit $0.000001 USD。 最终费用以账户适用价格及实际结算为准。 operationId: people-data-labs.enrich-person-data requestBody: required: true content: application/json: schema: type: object properties: lid: type: string examples: - '123456789' description: LinkedIn ID. name: type: string examples: - John Michael Doe description: Full name. email: type: string examples: - john.doe@example.com description: Email address. phone: type: string examples: - '+14155552671' description: Phone number; E.164 format recommended. pdl_id: type: string examples: - qEnxS5T1G2YvasA1x24qoA_0000 description: People Data Labs unique record ID. pretty: type: boolean default: true description: Format JSON response with indentation for readability. region: type: string examples: - CA description: State, province, or region of residence. school: type: string examples: - Stanford University description: School name attended. company: type: string examples: - Acme Corporation description: Company name where person has worked. country: type: string examples: - US - United States description: Country of residence (ISO 3166-1 alpha-2 code or full name). profile: type: string examples: - https://www.linkedin.com/in/john-doe - https://www.facebook.com/jane.doe description: Social profile URL (e.g., LinkedIn, Facebook). locality: type: string examples: - San Francisco description: City or locality of residence. location: type: string examples: - San Francisco, CA, USA description: General location (e.g., city, state, country). required: type: string examples: - emails AND phone_numbers - education AND (emails OR phone_numbers) - job_title AND job_company_name - experience AND work_email description: >- Boolean expression of top-level fields required in enriched profile for match. Use AND/OR operators and parentheses for logic (e.g., 'emails AND phone_numbers', 'education AND (emails OR phone_numbers)'). Valid fields: emails, phone_numbers, experience, education, job_title, job_company_name, full_name, location_country, work_email, personal_emails, mobile_phone, linkedin_url, profiles, skills, etc. last_name: type: string examples: - Doe description: Last name. birth_date: type: string examples: - '1990-01-15' description: Birth date (YYYY-MM-DD format). email_hash: type: string examples: - d41d8cd98f00b204e9800998ecf8427e - >- e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855 description: >- SHA-256 or MD5 hash of an email, for matching without exposing the raw email. first_name: type: string examples: - John description: First name. postal_code: type: string examples: - '94107' description: Postal or ZIP code of residence. data_include: type: string examples: - emails,phones,profiles - jobs,education description: >- Comma-separated data fields to include in response (e.g., 'emails,phones'). Refer to People Data Labs docs for all fields. min_likelihood: type: integer default: 2 maximum: 10 minimum: 0 examples: - 0 - 5 - 10 description: >- Minimum confidence score (0-10) for a match to be returned; higher is stricter. street_address: type: string examples: - 123 Main St description: Street address. include_if_matched: type: boolean default: false description: >- Include input parameters used for matching in the response if true. required: - email responses: '200': description: Tool result data content: application/json: schema: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__public_data default: content: application/json: schema: {} description: >- Error response; upstream passthrough responses may use provider formats x-codeSamples: - lang: text label: Reference example source: >- # Fixed reference example. Playground inputs do not update this sample. curl --request POST \ --url https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data \ --header 'Authorization: Bearer ' \ --header 'Content-Type: application/json' \ --data '{ "email": "john.doe@example.com" }' components: schemas: Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__public_data: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__fc7285c49c464f36 Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__fc7285c49c464f36: type: object required: - status - likelihood - data properties: data: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__801a7bed5bd96761 status: type: integer matched: type: array items: type: string likelihood: type: integer Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__801a7bed5bd96761: type: object properties: id: type: string sex: type: string emails: anyOf: - type: boolean - type: array items: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__52b88ac1067d4130 phones: type: array items: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__4b08c5750b3b38c4 skills: type: array items: type: string regions: anyOf: - type: boolean - type: array items: type: string summary: type: string headline: type: string industry: type: string profiles: type: array items: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__c09b76b3bd3d0fa9 countries: type: array items: type: string education: type: array items: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__599b93efe16611a5 full_name: type: string interests: type: array items: type: string job_title: type: string languages: type: array items: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__bc978d1b46ca644d last_name: type: string last_seen: type: string birth_date: anyOf: - type: boolean - type: string birth_year: anyOf: - type: boolean - type: integer experience: type: array items: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__2d7f961eac09b920 first_name: type: string first_seen: type: string github_url: type: string work_email: anyOf: - type: boolean - type: string facebook_id: type: string job_history: type: array items: {} job_summary: type: string linkedin_id: type: string middle_name: type: string num_records: type: integer num_sources: type: integer twitter_url: type: string facebook_url: type: string last_initial: type: string linkedin_url: type: string location_geo: anyOf: - type: boolean - type: string mobile_phone: anyOf: - type: boolean - type: string name_aliases: type: array items: type: string first_initial: type: string job_onet_code: type: string location_name: anyOf: - type: boolean - type: string phone_numbers: anyOf: - type: boolean - type: array items: type: string certifications: type: array items: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__e96325452eab319c job_company_id: type: string job_start_date: type: string job_title_role: type: string location_metro: anyOf: - type: boolean - type: string location_names: anyOf: - type: boolean - type: array items: type: string middle_initial: type: string dataset_version: type: string github_username: type: string inferred_salary: type: string job_title_class: type: string location_region: anyOf: - type: boolean - type: string personal_emails: anyOf: - type: boolean - type: array items: type: string possible_emails: type: array items: {} possible_phones: type: array items: {} facebook_friends: type: integer job_company_name: type: string job_company_size: type: string job_company_type: type: string job_last_changed: type: string job_title_levels: type: array items: type: string location_country: type: string street_addresses: anyOf: - type: boolean - type: array items: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__dcb5667b12edf989 twitter_username: type: string facebook_username: type: string job_last_verified: type: string linkedin_username: type: string location_locality: anyOf: - type: boolean - type: string possible_profiles: type: array items: {} job_company_ticker: type: string job_title_sub_role: type: string location_continent: type: string job_company_founded: type: integer job_company_website: type: string job_company_industry: type: string job_onet_major_group: type: string job_onet_minor_group: type: string linkedin_connections: type: integer location_postal_code: anyOf: - type: boolean - type: string possible_birth_dates: type: array items: type: string location_last_updated: type: string job_company_industry_v2: type: string job_company_linkedin_id: type: string job_company_twitter_url: type: string location_address_line_2: type: string location_street_address: anyOf: - type: boolean - type: string possible_location_names: type: array items: type: string job_company_facebook_url: type: string job_company_linkedin_url: type: string job_company_location_geo: type: string inferred_years_experience: type: integer job_company_location_name: type: string job_onet_broad_occupation: type: string possible_street_addresses: type: array items: {} job_company_employee_count: type: integer job_company_location_metro: type: string recommended_personal_email: anyOf: - type: boolean - type: string job_company_location_region: type: string job_company_inferred_revenue: type: string job_company_location_country: type: string job_onet_specific_occupation: type: string job_company_location_locality: type: string job_company_location_continent: type: string job_company_location_postal_code: type: string job_company_total_funding_raised: type: integer job_company_location_address_line_2: type: string job_company_location_street_address: type: string job_onet_specific_occupation_detail: type: string job_company_12mo_employee_growth_rate: type: number Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__52b88ac1067d4130: type: object properties: type: type: string address: type: string md5_hash: type: string last_seen: type: string first_seen: type: string num_sources: type: integer sha_256_hash: type: string Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__4b08c5750b3b38c4: type: object properties: number: type: string last_seen: type: string first_seen: type: string num_sources: type: integer Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__c09b76b3bd3d0fa9: type: object properties: id: type: string url: type: string network: type: string username: type: string last_seen: type: string first_seen: type: string num_sources: type: integer Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__599b93efe16611a5: type: object properties: gpa: type: number raw: type: array items: type: string majors: type: array items: type: string minors: type: array items: type: string school: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__9cb4ca9b3fb6f2eb degrees: type: array items: type: string summary: type: string end_date: type: string start_date: type: string Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__bc978d1b46ca644d: type: object properties: name: type: string proficiency: type: integer Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__2d7f961eac09b920: type: object properties: title: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__da280d167e6b8aed company: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__74fd576ca6841cee summary: type: string end_date: type: string last_seen: type: string first_seen: type: string is_primary: type: boolean start_date: type: string num_sources: type: integer location_names: type: array items: type: string Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__e96325452eab319c: type: object properties: name: type: string end_date: type: string start_date: type: string organization: type: string Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__dcb5667b12edf989: type: object properties: geo: type: string name: type: string metro: type: string region: type: string country: type: string locality: type: string continent: type: string last_seen: type: string first_seen: type: string num_sources: type: integer postal_code: type: string address_line_2: type: string street_address: type: string Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__9cb4ca9b3fb6f2eb: type: object properties: id: type: string raw: type: array items: type: string name: type: string type: type: string domain: type: string website: type: string location: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__0b1549661314d92d linkedin_id: type: string twitter_url: type: string facebook_url: type: string linkedin_url: type: string Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__da280d167e6b8aed: type: object properties: raw: type: array items: type: string name: type: string role: type: string class: type: string levels: type: array items: type: string sub_role: type: string Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__74fd576ca6841cee: type: object properties: id: type: string raw: type: array items: type: string name: type: string size: type: string type: type: string ticker: type: string founded: type: integer website: type: string industry: type: string location: $ref: >- #/components/schemas/Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__0b1549661314d92d fuzzy_match: type: boolean industry_v2: type: string linkedin_id: type: string twitter_url: type: string facebook_url: type: string linkedin_url: type: string Response576A0Ea506F3_connect_PEOPLEDATALABS_ENRICH_PERSON_DATA__output__0b1549661314d92d: type: object properties: geo: type: string name: type: string metro: type: string region: type: string country: type: string locality: type: string continent: type: string last_seen: type: string first_seen: type: string num_sources: type: integer postal_code: type: string address_line_2: type: string street_address: type: string securitySchemes: bearerAuth: scheme: bearer type: http ```` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.