prospeo-search-api
Skill759 starsChanged 28 days agoMITView on GitHub
This skill should be used when searching for people/leads using the Prospeo Search Person API. It provides the correct API format, filter types, rate limiting patterns, and state-by-state crawling techniques to overcome the 25K result limit. Use when building lead lists, searching by job title/industry/location, or integrating with Prospeo.
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We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
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1
Very specific
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- Common
- Distinctive
- Very specific
- Distinctive: line 12
Use this skill when:
- Very specific: line 305
Use null (or omit) to ignore recency and match any company currently at the given stage.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Prospeo Search Person API
This skill documents how to use the Prospeo Search Person API for finding leads with filters.
When to Use
Use this skill when:
- Searching for people/leads by job title, industry, location, company size, etc.
- Building lead lists from Prospeo's database
- Running large US-wide searches that need state-by-state crawling
API Overview
Endpoint: POST https://api.prospeo.io/search-person
Authentication: X-KEY header with API key
Rate Limits:
- 2-2.5 requests/second (120-150 req/min)
- Token bucket implementation recommended
Result Limits:
- 25 results per page
- 1000 pages max = 25,000 results per search
- 1 credit per search request that returns at least 1 result
Request Format
POST /search-person
Headers: {
'Content-Type': 'application/json',
'X-KEY': process.env.PROSPEO_API_KEY
}
Body: {
page: number, // 1-1000
filters: ProspeoSearchFilters
}Filter Types
interface ProspeoSearchFilters {
// Location (use "State, United States #US" format)
person_location_search?: {
include?: string[]; // e.g., ["California, United States #US"]
exclude?: string[];
};
// Job titles
person_job_title?: {
include?: string[]; // e.g., ["CEO", "Founder"]
exclude?: string[];
match_only_exact_job_titles?: boolean;
};
// Company size
company_headcount_custom?: {
min?: number; // e.g., 11
max?: number; // e.g., 500
};
// Industry
company_industry?: {
include?: string[]; // e.g., ["Information Technology"]
exclude?: string[];
};
// Technology stack
company_technology?: {
include?: string[]; // e.g., ["Salesforce", "HubSpot"]
exclude?: string[];
};
// Contact requirements
person_contact_details?: {
email?: string[]; // ["VERIFIED"] for verified emails only
mobile?: string[];
operator?: string;
};
// Duplicate control
person_duplicate_control?: {
hide_people_from_all_my_lists?: boolean;
hide_people_already_exported_before?: boolean;
};
// Funding (use this for "recently raised Series X" targeting)
company_funding?: {
// Days since last funding round. Valid values: 90, 180, 270, 365, or null (None).
// Maps to UI dropdown "Select last funding round date".
funding_date?: 90 | 180 | 270 | 365 | null;
// Last funding round amount (bucketed enum range).
// Valid bucket values: "<100K", "100K-500K", "500K-1M", "1M-5M", "5M-10M",
// "10M-25M", "25M-50M", "50M-100M", "100M-500M", "500M+", "Max"
last_funding?: { min?: string; max?: string } | null;
// Total funding raised across all rounds (same bucketed enum range as last_funding).
total_funding?: { min?: string; max?: string };
// Funding stage checkboxes. Valid values:
// "Pre seed", "Seed", "Series unknown", "Series A", "Series B",
// "Series C", "Series D", "Series E-J",
// "Grant", "Angel", "Private equity", "Debt financing",
// "Non equity assistance", "Post IPO equity", "Undisclosed",
// "Post IPO debt", "Product crowdfunding", "Equity crowdfunding",
// "Corporate round", "Convertible note", "Secondary market",
// "Initial coin offering", "Post IPO secondary"
stage?: string[];
};
// Company filters
company_name?: { include?: string[]; exclude?: string[] };
company_domain?: { include?: string[]; exclude?: string[] };
company_revenue_custom?: { min?: number; max?: number };
company_founding_year?: { min?: number; max?: number };
}Response Format
interface ProspeoSearchApiResponse {
error: boolean;
message?: string;
results?: ProspeoSearchResult[];
pagination?: {
current_page: number;
total_page: number;
total_count: number;
per_page: number; // Always 25
};
}
interface ProspeoSearchResult {
person: {
person_id: string;
first_name?: string;
last_name?: string;
full_name?: string;
current_job_title?: string;
linkedin_url?: string;
email?: string;
email_status?: string;
phone?: string;
location?: {
city?: string;
state?: string;
country?: string;
};
job_history?: Array<{
title?: string;
company_name?: string;
current?: boolean;
}>;
};
company?: {
company_id?: string;
name?: string;
domain?: string;
linkedin_url?: string;
industry?: string;
headcount?: number;
headcount_range?: string;
technologies?: string[];
location?: { city?: string; state?: string; country?: string };
};
}State-by-State Crawling Pattern
For US-wide searches exceeding 25K results, split by state:
const US_STATES_BY_SIZE = [
'California', 'Texas', 'Florida', 'New York', 'Illinois', 'Pennsylvania',
'Ohio', 'Georgia', 'North Carolina', 'Michigan', 'New Jersey', 'Virginia',
'Washington', 'Arizona', 'Massachusetts', 'Tennessee', 'Indiana', 'Missouri',
'Maryland', 'Wisconsin', 'Colorado', 'Minnesota', 'South Carolina', 'Alabama',
'Louisiana', 'Kentucky', 'Oregon', 'Oklahoma', 'Connecticut', 'Utah', 'Iowa',
'Nevada', 'Arkansas', 'Mississippi', 'Kansas', 'New Mexico', 'Nebraska',
'Idaho', 'West Virginia', 'Hawaii', 'New Hampshire', 'Maine', 'Montana',
'Rhode Island', 'Delaware', 'South Dakota', 'North Dakota', 'Alaska',
'Vermont', 'Wyoming'
];
// Format for location filter
function formatStateLocation(state: string): string {
return `${state}, United States #US`;
}
// Replace "United States #US" with state-specific location
function createStateFilters(baseFilters, state) {
const stateFilters = JSON.parse(JSON.stringify(baseFilters));
stateFilters.person_location_search.include =
stateFilters.person_location_search.include.map(loc =>
loc === 'United States #US' ? formatStateLocation(state) : loc
);
return stateFilters;
}Rate Limiting Implementation
// Token bucket rate limiter
class TokenBucket {
private tokens: number;
private lastRefill: number;
private maxTokens = 5;
private refillRate = 2.0; // tokens per second
async acquire(): Promise<void> {
this.refill();
if (this.tokens >= 1) {
this.tokens -= 1;
return;
}
const waitMs = Math.ceil(((1 - this.tokens) / this.refillRate) * 1000);
await this.sleep(Math.max(waitMs, 500));
this.refill();
this.tokens -= 1;
}
}Error Handling
// Retry on 429 with exponential backoff
if (status === 429 && retryCount < 5) {
const backoffMs = Math.min(2000 * Math.pow(2, retryCount), 60000);
await sleep(backoffMs);
return searchPeople(filters, page, retryCount + 1);
}Example: Search for Tech Executives
const filters: ProspeoSearchFilters = {
person_location_search: {
include: ['United States #US']
},
person_job_title: {
include: ['CEO', 'CTO', 'VP Engineering', 'Head of Engineering'],
match_only_exact_job_titles: false
},
company_headcount_custom: {
min: 11,
max: 500
},
company_industry: {
include: ['Information Technology', 'Software']
},
person_contact_details: {
email: ['VERIFIED']
}
};
const service = new ProspeoSearchService();
const { results, summary } = await service.searchWithStateSplitting(filters, {
maxTotalContacts: 10000,
maxContactsPerState: 5000
});Example: Recently Raised Series A
Target marketing leaders at US software companies (50–200 employees) that raised Series A in the last 180 days:
const filters: ProspeoSearchFilters = {
person_location_search: { include: ['United States #US'] },
person_job_title: {
include: [
'CMO', 'Chief Marketing Officer',
'VP Marketing', 'Vice President Marketing',
'Head Marketing', 'Director Marketing',
'Growth', 'VP Growth', 'Head Growth'
]
},
company_headcount_custom: { min: 50, max: 200 },
company_industry: {
include: ['Software Development', 'Computer Software', 'Information Technology & Services']
},
company_funding: {
funding_date: 180,
stage: ['Series A']
},
person_contact_details: { email: ['VERIFIED'] }
};Set funding_date to 90 / 180 / 270 / 365 for tighter or looser recency windows.
Use null (or omit) to ignore recency and match any company currently at the given stage.
Working implementations in this repo
/prospeo-full-export— the search + paginated export scripts built on these filters/list-expanderscripts/pull.ts— the same filters, used for wide TAM pulls/list-builder— orchestrates both as one lane of a larger list build
Environment Variables
PROSPEO_API_KEY=your_api_key_hereWhat to do next
This is a reference skill — no direct next step. Used by /prospeo-full-export and /auto-research-public to build the actual search.
Return to the skill that sent you here.
Related skills
/prospeo-full-export— the main consumer of this reference/auto-research-public— also uses Prospeo search via phase-prospeo.ts
Other versions1 project uses a version of this.
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Edited · 1
- automatewithuday/GTM-Skills★ 189% same
Wrote their own version · 0
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How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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