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Nyne Search

Search for people using natural language queries with the Nyne Search API. Find professionals by role, company, location, industry, or any combination. Suppo...

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Search for people using natural language queries with the Nyne Search API. Find professionals by role, company, location, industry, or any combination. Suppo...

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

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Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
SKILL.md

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Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

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I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

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I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 32 sections Open source page

Nyne Search Skill

Search for people using natural language queries. Find professionals by role, company, location, industry, or any combination. Returns matching profiles with contact info, work history, education, and optional AI relevance scoring. Important: This API is async. You POST to submit, get a request_id, then poll GET until status: "completed". Light searches complete in 3-40 seconds; premium searches take 30-300 seconds.

Agent Instructions

When presenting search results to the user, show all returned data for each person. Walk through: Result count โ€” total_stored, total_estimate, has_more, credits_charged Each person โ€” displayname, headline, bio, location, gender, estimated_age, total_experience_years, is_decision_maker Contact info โ€” best_business_email, best_personal_email, altemails, fullphone (if show_emails/show_phone_numbers were enabled) Social profiles โ€” LinkedIn URL, username, connections, followers Work history โ€” all organizations with title, dates, company details (industries, num_employees, funding, technologies) Education โ€” schools with degree, major, dates; note is_top_universities flag Interests โ€” work interests and certifications Patents โ€” title, date, reference, URL (if present) Languages โ€” spoken languages Score โ€” AI relevance score 0-1 (if profile_scoring was enabled) Insights โ€” AI-generated match reasoning (if insights were enabled) If has_more is true, tell the user there are more results available and offer to paginate using the next_cursor. If a field is missing from the response, it means no data was found โ€” skip it silently.

Setup

Required environment variables: NYNE_API_KEY โ€” your Nyne API key NYNE_API_SECRET โ€” your Nyne API secret Get credentials at https://api.nyne.ai. export NYNE_API_KEY="your-api-key" export NYNE_API_SECRET="your-api-secret" Verify they're set: echo "Key: ${NYNE_API_KEY:0:8}... Secret: ${NYNE_API_SECRET:0:6}..."

Important: JSON Handling

The API response can contain control characters in JSON string values that break jq. All examples use a nyne_parse helper that cleans and re-encodes JSON via python3. Define it once per session: nyne_parse() { python3 -c " import sys, json, re raw = sys.stdin.read() clean = re.sub(r'[\x00-\x1f]+', ' ', raw) data = json.loads(clean) json.dump(data, sys.stdout) " }

Quick Start

Search for people by natural language query and poll until complete: nyne_parse() { python3 -c " import sys, json, re raw = sys.stdin.read() clean = re.sub(r'[\x00-\x1f]+', ' ', raw) data = json.loads(clean) json.dump(data, sys.stdout) " } # Submit search request curl -s -X POST "https://api.nyne.ai/person/search" \ -H "Content-Type: application/json" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" \ -d '{"query": "Software engineers at Google in San Francisco", "limit": 10, "type": "premium", "show_emails": true}' | nyne_parse > /tmp/nyne_search.json STATUS=$(jq -r '.data.status' /tmp/nyne_search.json) if [ "$STATUS" = "completed" ]; then echo "Search completed immediately." jq '.data | {total_stored, total_estimate, has_more, credits_charged}' /tmp/nyne_search.json jq '.data.results[] | {displayname, headline, location}' /tmp/nyne_search.json else REQUEST_ID=$(jq -r '.data.request_id' /tmp/nyne_search.json) echo "Request submitted: $REQUEST_ID (status: $STATUS)" # Poll until complete (checks every 5s, times out after 10 min) SECONDS_WAITED=0 while [ $SECONDS_WAITED -lt 600 ]; do curl -s "https://api.nyne.ai/person/search?request_id=$REQUEST_ID" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" | nyne_parse > /tmp/nyne_search.json STATUS=$(jq -r '.data.status' /tmp/nyne_search.json) echo "Status: $STATUS ($SECONDS_WAITED seconds elapsed)" if [ "$STATUS" = "completed" ]; then jq '.data | {total_stored, total_estimate, has_more, credits_charged}' /tmp/nyne_search.json jq '.data.results[] | {displayname, headline, location}' /tmp/nyne_search.json break elif [ "$STATUS" = "failed" ]; then echo "Search failed." jq . /tmp/nyne_search.json break fi sleep 5 SECONDS_WAITED=$((SECONDS_WAITED + 5)) done if [ $SECONDS_WAITED -ge 600 ]; then echo "Timed out after 10 minutes. Resume polling with request_id: $REQUEST_ID" fi fi

Submit Search (POST)

Endpoint: POST https://api.nyne.ai/person/search Headers: Content-Type: application/json X-API-Key: $NYNE_API_KEY X-API-Secret: $NYNE_API_SECRET

Query Parameters

ParameterTypeDefaultDescriptionquerystringrequiredNatural language search query (max 1000 chars). Examples: "Software engineers at Microsoft in Seattle", "Marketing directors at Fortune 500"typestring"premium"Search quality tier: "light" (fast, 3-40s), "medium" (balanced), "premium" (best quality, 30-300s)limitinteger10Results per request (max 100)offsetinteger0Starting position, 0-indexed (max 999). offset + limit must be โ‰ค 1000show_emailsbooleanfalseInclude email addresses in results (+2 credits). Significantly increases latency โ€” search will take longer to complete as emails are enriched per resultshow_phone_numbersbooleanfalseInclude phone numbers in results (+14 credits). Significantly increases latency โ€” search will take longer to complete as phone numbers are enriched per resultrequire_emailsbooleanfalseOnly return profiles that have email addresses (+1 credit)require_phone_numbersbooleanfalseOnly return profiles that have phone numbers (+1 credit)require_phones_or_emailsbooleanfalseOnly return profiles with either phone or email (+1 credit)insightsbooleanfalseAI-generated insights per result explaining match relevance (+1 credit per result). Not available for light typeprofile_scoringbooleanfalseInclude AI relevance score (0-1) per result (+1 credit)high_freshnessbooleanfalsePrioritize recently updated profiles (+2 credits). Not available for light typeforce_newbooleanfalseForce fresh search, ignore cached resultscustom_filtersobjectomitStructured filters for precise targeting (see Custom Filters below)callback_urlstringomitWebhook URL for async results delivery

Custom Filters

Pass as a custom_filters object to narrow results beyond the natural language query. Array fields (pass as arrays of strings): FilterDescriptionlocationsGeographic locations (e.g., ["San Francisco", "New York"])languagesLanguages spoken (e.g., ["English", "Spanish"])titlesJob titles (e.g., ["CTO", "VP Engineering"])industriesIndustry sectors (e.g., ["Technology", "Healthcare"])companiesCompany names, current or past (e.g., ["Google", "Meta"])universitiesUniversities attended (e.g., ["Stanford", "MIT"])keywordsProfile keywords (e.g., ["machine learning", "AI"])degreesEducation degrees (e.g., ["bachelor", "master", "phd"])specialization_categoriesAcademic specialization categories Numeric range fields (pass as integers): FilterDescriptionmin_linkedin_followers / max_linkedin_followersLinkedIn follower count rangemin_total_experience_years / max_total_experience_yearsTotal work experience rangemin_current_experience_years / max_current_experience_yearsCurrent role tenure rangemin_estimated_age / max_estimated_ageEstimated age range Exact match fields: FilterTypeDescriptionfirst_namestringExact first name matchmiddle_namestringExact middle name matchlast_namestringExact last name matchgenderstring"male" or "female"studied_at_top_universitiesbooleanAttended a top-ranked university

Examples

Basic search: curl -s -X POST "https://api.nyne.ai/person/search" \ -H "Content-Type: application/json" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" \ -d '{"query": "Software engineers at Google in San Francisco", "limit": 10}' | nyne_parse > /tmp/nyne_search.json jq '{status: .data.status, request_id: .data.request_id}' /tmp/nyne_search.json With emails and phone numbers: curl -s -X POST "https://api.nyne.ai/person/search" \ -H "Content-Type: application/json" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" \ -d '{"query": "Marketing directors at tech startups in Austin", "limit": 25, "show_emails": true, "show_phone_numbers": true}' | nyne_parse > /tmp/nyne_search.json With custom filters: curl -s -X POST "https://api.nyne.ai/person/search" \ -H "Content-Type: application/json" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" \ -d '{ "query": "Engineering leaders in fintech", "limit": 20, "type": "premium", "show_emails": true, "custom_filters": { "locations": ["New York", "San Francisco"], "titles": ["CTO", "VP Engineering", "Head of Engineering"], "min_total_experience_years": 10, "industries": ["Financial Services", "Technology"] } }' | nyne_parse > /tmp/nyne_search.json Light search (fast, 1 credit): curl -s -X POST "https://api.nyne.ai/person/search" \ -H "Content-Type: application/json" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" \ -d '{"query": "Data scientists at Amazon", "type": "light", "limit": 10}' | nyne_parse > /tmp/nyne_search.json With AI scoring and insights: curl -s -X POST "https://api.nyne.ai/person/search" \ -H "Content-Type: application/json" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" \ -d '{"query": "AI researchers in healthcare", "type": "premium", "profile_scoring": true, "insights": true, "limit": 10}' | nyne_parse > /tmp/nyne_search.json With freshness priority: curl -s -X POST "https://api.nyne.ai/person/search" \ -H "Content-Type: application/json" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" \ -d '{"query": "Product managers who recently changed jobs", "type": "premium", "high_freshness": true, "show_emails": true}' | nyne_parse > /tmp/nyne_search.json Require contact info: curl -s -X POST "https://api.nyne.ai/person/search" \ -H "Content-Type: application/json" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" \ -d '{"query": "Sales directors at SaaS companies", "require_emails": true, "show_emails": true, "limit": 50}' | nyne_parse > /tmp/nyne_search.json Submit response: { "success": true, "data": { "request_id": "abc12345_1737123456_1234", "status": "completed", "results": [...], "offset": 0, "limit": 10, "total_stored": 47, "total_estimate": 2500, "has_more": true, "next_cursor": "eyJvIjoxMCwiciI6ImFiYzEyMzQ1XzE3MzcxMjM0NTZfMTIzNCJ9", "from_cache": false, "credits_charged": 7 }, "timestamp": "2026-02-19T..." } Note: The POST may return status: "completed" immediately (especially for cached or light searches) or status: "processing" requiring polling. Always check the status.

Poll for Results (GET)

Endpoint: GET https://api.nyne.ai/person/search?request_id={id} Headers: Same X-API-Key and X-API-Secret as above.

Check status once

curl -s "https://api.nyne.ai/person/search?request_id=$REQUEST_ID" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" | nyne_parse > /tmp/nyne_search.json jq '{status: .data.status, total_stored: .data.total_stored}' /tmp/nyne_search.json

Full polling loop

SECONDS_WAITED=0 TIMEOUT=600 # 10 minutes while [ $SECONDS_WAITED -lt $TIMEOUT ]; do curl -s "https://api.nyne.ai/person/search?request_id=$REQUEST_ID" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" | nyne_parse > /tmp/nyne_search.json STATUS=$(jq -r '.data.status' /tmp/nyne_search.json) echo "[$(date +%H:%M:%S)] Status: $STATUS ($SECONDS_WAITED s)" case "$STATUS" in completed) jq '.data | {total_stored, total_estimate, has_more, credits_charged}' /tmp/nyne_search.json jq '.data.results[] | {displayname, headline, location}' /tmp/nyne_search.json break ;; failed) echo "Search failed:" jq '.data' /tmp/nyne_search.json break ;; *) sleep 5 SECONDS_WAITED=$((SECONDS_WAITED + 5)) ;; esac done if [ "$STATUS" != "completed" ] && [ "$STATUS" != "failed" ]; then echo "Timed out. Resume polling with request_id: $REQUEST_ID" fi

Pagination

After the initial search completes, paginate through results for free (cached results, no additional credits).

Cursor-based pagination (recommended)

Use the next_cursor from the previous response: curl -s -X POST "https://api.nyne.ai/person/search" \ -H "Content-Type: application/json" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" \ -d '{"cursor": "eyJvIjoxMCwiciI6ImFiYzEyMzQ1XzE3MzcxMjM0NTZfMTIzNCJ9"}' | nyne_parse > /tmp/nyne_search.json jq '.data | {total_stored, offset, limit, has_more}' /tmp/nyne_search.json jq '.data.results[] | {displayname, headline, location}' /tmp/nyne_search.json

Offset-based pagination

Use request_id + offset from the original search: curl -s -X POST "https://api.nyne.ai/person/search" \ -H "Content-Type: application/json" \ -H "X-API-Key: $NYNE_API_KEY" \ -H "X-API-Secret: $NYNE_API_SECRET" \ -d '{"request_id": "abc12345_1737123456_1234", "offset": 25, "limit": 25}' | nyne_parse > /tmp/nyne_search.json jq '.data | {total_stored, offset, limit, has_more}' /tmp/nyne_search.json jq '.data.results[] | {displayname, headline, location}' /tmp/nyne_search.json Pagination notes: Paginating through cached results is free โ€” no additional credits charged Maximum 1000 results per search (offset + limit โ‰ค 1000) has_more indicates whether more results are available next_cursor is only present when has_more is true Results are cached for 30 days

Response Structure

When status is completed: { "success": true, "timestamp": "2026-02-19T...", "data": { "request_id": "abc12345_1737123456_1234", "status": "completed", "results": [ { "displayname": "Jane Smith", "headline": "Senior Software Engineer at Google", "bio": "...", "location": "San Francisco, CA", "gender": "female", "estimated_age": 35, "total_experience_years": 12, "is_decision_maker": 1, "is_top_universities": true, "languages": ["English", "Spanish"], "interests": { "work": ["software engineering", "machine learning", "distributed systems"], "certification": ["AWS Solutions Architect"] }, "patents": [], "best_business_email": "jane@google.com", "best_personal_email": "jane@gmail.com", "altemails": ["j.smith@gmail.com"], "fullphone": [{"fullphone": "+14155551234", "type": "mobile"}], "social_profiles": { "linkedin": { "url": "https://www.linkedin.com/in/janesmith", "username": "janesmith", "connections": 1243, "followers": 542, "photo_url": "..." } }, "organizations": [ { "name": "Google", "title": "Senior Software Engineer", "startDate": "3-2020", "location": "San Francisco", "company_website": "google.com", "industries": ["Technology"], "num_employees": "10001+" } ], "schools_attended": ["Stanford University"], "schools_info": [ { "name": "Stanford University", "degree": "Master's", "title": "Computer Science", "startDate": "2012", "endDate": "2014" } ], "score": 0.92, "insights": { "match_reasoning": "Strong match based on..." } } ], "offset": 0, "limit": 10, "total_stored": 47, "total_estimate": 2500, "has_more": true, "next_cursor": "eyJvIjoxMCwi...", "from_cache": false, "credits_charged": 7 } }

Result Fields

FieldTypeDescriptiondisplaynamestringPerson's full nameheadlinestringCurrent job title/headlinebiostringProfessional biographylocationstringGeographic locationgenderstring"male" or "female"estimated_ageintegerEstimated agetotal_experience_yearsintegerYears of total work experienceis_decision_makerintegerWhether person holds decision-making authority (1 = yes)is_top_universitiesbooleanWhether person attended a top-ranked universitylanguagesarrayLanguages spoken (array of strings)interestsobject{work: [...], certification: [...]} โ€” work interests and certificationspatentsarrayPatents held: {title, description, date, reference, url}best_business_emailstringPrimary business email (requires show_emails: true)best_personal_emailstringPrimary personal email (requires show_emails: true)altemailsarrayAlternative email addresses (requires show_emails: true)fullphonearrayPhone numbers with type (requires show_phone_numbers: true). Each: {fullphone, type}social_profilesobjectSocial profile data (see below)organizationsarrayWork history (see below)schools_attendedarrayUniversity names as stringsschools_infoarrayDetailed education: {name, degree, major, startDate, endDate}scorenumberAI relevance score 0-1 (requires profile_scoring: true)insightsobjectAI-generated match reasoning (requires insights: true)

Social Profiles Object

{ "linkedin": { "url": "https://www.linkedin.com/in/...", "username": "...", "connections": 1243, "followers": 542, "photo_url": "..." } }

Organization Object

{ "name": "Windfall Bio", "title": "Vice President of Software Engineering", "startDate": "2024-08-01", "endDate": null, "location": "San Mateo, California, United States", "company_website": "http://www.windfall.bio", "company_linkedin_url": "https://www.linkedin.com/company/windfallbio", "company_domain": "windfall.bio", "industries": ["Manufacturing"], "num_employees": 37, "num_employees_range": "11-50", "is_startup": true, "is_b2b": true, "is_b2c": false, "is_saas": false, "founded_in": 2022, "latest_funding_round": "Series A", "latest_funding_amount": 28000000, "funding_total_usd": 37000000, "annual_revenue": 345000, "specialties": ["methane", "climate", "agtech"], "technologies": ["Google Analytics", "AWS Lambda", "Webflow"], "companyDesc": "...", "logo_url": "..." } Organizations include rich company intelligence: funding data, tech stack, employee counts, and B2B/B2C/SaaS flags. Not all fields are present for every organization.

Response Metadata Fields

FieldTypeDescriptiontotal_storedintegerNumber of results stored from this searchtotal_estimateintegerEstimated total matching profileshas_morebooleanWhether more results are available for paginationnext_cursorstringOpaque pagination token for next page (present when has_more is true)from_cachebooleanWhether results came from cache (30-day TTL)credits_chargedintegerTotal credits charged for this requestoffsetintegerCurrent offset in result setlimitintegerResults per page

Useful jq Filters

After polling completes, the clean response is at /tmp/nyne_search.json: # Search metadata jq '.data | {total_stored, total_estimate, has_more, credits_charged, from_cache}' /tmp/nyne_search.json # List all people (name + headline + location) jq '.data.results[] | {displayname, headline, location}' /tmp/nyne_search.json # All emails jq '.data.results[] | {displayname, best_business_email, best_personal_email, altemails}' /tmp/nyne_search.json # Phone numbers jq '.data.results[] | {displayname, fullphone}' /tmp/nyne_search.json # LinkedIn profiles jq '.data.results[] | {displayname, linkedin: .social_profiles.linkedin.url}' /tmp/nyne_search.json # Work history per person jq '.data.results[] | {displayname, orgs: [.organizations[] | {name, title}]}' /tmp/nyne_search.json # Decision makers only jq '[.data.results[] | select(.is_decision_maker == true)] | length' /tmp/nyne_search.json jq '[.data.results[] | select(.is_decision_maker == true) | {displayname, headline}]' /tmp/nyne_search.json # Sort by relevance score (if profile_scoring enabled) jq '[.data.results | sort_by(-.score)[] | {displayname, headline, score}]' /tmp/nyne_search.json # Experience range jq '.data.results[] | {displayname, total_experience_years} | select(.total_experience_years >= 10)' /tmp/nyne_search.json # Education jq '.data.results[] | {displayname, schools: .schools_attended}' /tmp/nyne_search.json # Interests and certifications jq '.data.results[] | {displayname, work_interests: .interests.work, certifications: .interests.certification}' /tmp/nyne_search.json # Patents jq '.data.results[] | select(.patents | length > 0) | {displayname, patents: [.patents[] | {title, date}]}' /tmp/nyne_search.json # Company intelligence (funding, tech stack) jq '.data.results[] | {displayname, companies: [.organizations[] | {name, funding_total_usd, latest_funding_round, num_employees, is_startup}]}' /tmp/nyne_search.json # Get next_cursor for pagination jq -r '.data.next_cursor' /tmp/nyne_search.json # Count results jq '.data.results | length' /tmp/nyne_search.json

Error Handling

HTTP CodeErrorDescription400invalid_parametersInvalid parameter value or missing query400invalid_custom_filtersMalformed custom_filters object401invalid_credentialsInvalid API key/secret404request_not_foundInvalid request_id for status check (GET only)429rate_limit_exceededToo many requests429insufficient_creditsNot enough credits for this search500internal_errorServer error

Fast Search โ€” type: "light" (1 credit per result)

Basic search with fast results in 3-40 seconds. Best for quick lookups when you need a broad list of names and don't need deep profile data. AI features (insights, high_freshness) are NOT available for light type. Profile scoring is available. {"query": "Software engineers at Google", "type": "light", "limit": 50}

Smart Search โ€” type: "medium"

Balanced tier between speed and quality. Use when you want better matching than light but don't need the full depth of premium. Supports all AI features. {"query": "Engineering managers in fintech", "type": "medium", "limit": 25}

Pro Search โ€” type: "premium" (5 credits per result)

Comprehensive search taking 30-300 seconds. Best quality results with deepest profile matching. Required for maximum-quality insights and high_freshness results. Use when result quality matters more than speed. {"query": "AI researchers at top universities", "type": "premium", "limit": 10, "insights": true, "profile_scoring": true}

AI-Powered Analysis Features

These features add intelligence on top of search results. Insights and High Freshness are NOT available for light type searches โ€” use medium or premium.

Query Insights (insights: true, +1 credit per result)

AI-generated analysis for each result explaining why this person matches your search query. Returns structured reasoning about the match relevance โ€” how their background, role, and experience align with what you're looking for. Invaluable for qualifying leads or evaluating candidates at scale. Use when you need to understand the "why" behind each match, not just the "who". {"query": "AI researchers in healthcare", "type": "premium", "insights": true, "limit": 10}

Profile Scoring (profile_scoring: true, +1 credit)

AI relevance scoring that assigns each result a score from 0 to 1, where 1.0 is a perfect match. Use to rank and prioritize results by relevance. Works with all search tiers including light. Combine with insights for both a score and an explanation. {"query": "Senior engineers at fintech startups", "profile_scoring": true, "limit": 25}

High Freshness (high_freshness: true, +2 credits)

Prioritizes profiles that have been recently updated โ€” people who recently changed jobs, updated their LinkedIn, or have fresh activity. Use when recency matters: hiring recently active candidates, targeting people who just moved to a new role, or finding profiles with current contact info. Not available for light type. {"query": "Product managers who recently changed jobs", "type": "premium", "high_freshness": true, "show_emails": true}

Combining AI Features

Stack insights + scoring + freshness for maximum intelligence: { "query": "VP of Engineering at Series B startups in San Francisco", "type": "premium", "insights": true, "profile_scoring": true, "high_freshness": true, "show_emails": true, "limit": 10 }

Credit Costs

Credits are charged based on features used per request. Pagination within cached results is free. FeatureCreditsDescriptionFast Search (type: "light")1Basic search, fastest response (3-40 seconds)Pro Search (type: "premium")5Comprehensive search, best quality (30-300 seconds)Smart Ranking (profile_scoring, boolean)1AI-powered relevance scoring of resultsCandidate Insights (insights, boolean)1AI-generated insights about each resultRealtime Profiles (high_freshness, boolean)2Prioritize recently updated profilesFilter Without Contact Data1Search without email/phone enrichmentEnrich Phones (show_phone_numbers, boolean)14Include phone numbers in results. Significantly increases latencyEnrich Emails (show_emails, boolean)2Include email addresses in results. Significantly increases latencyRequire Emails (require_emails, boolean)1Only return profiles with email addressesRequire Phones (require_phone_numbers, boolean)1Only return profiles with phone numbersRequire Contact Info (require_phones_or_emails, boolean)1Only return profiles with phone OR emailPagination (cached)0Free after initial search (30-day cache)

Rate Limits

Per minute: 60 requests Per hour: 1,000 requests Monthly: Plan-dependent

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
1 Docs
  • SKILL.md Primary doc