# AGENTS.md - Daemon Data actors on Apify

Machine-readable notes for AI agents, coding assistants and MCP clients that need structured data from the France-focused public Welcome to the Jungle board, Indian job boards, Oracle Recruiting Cloud career sites, Indian IPO/stock sources, the Dubai Land Department, The Gazette (UK insolvency) or Luma (lu.ma) events. All actors are published by `data_daemon` on Apify Store (https://apify.com/data_daemon), run on Apify's platform, read each site's own JSON endpoints (no login, no proxy), and charge per record returned. Prices below are list prices on 2026-10-18 (Foundit and Luma: 2026-10-21); the actor page shows the price for the user's plan. Input examples marked "verified" returned data on the date shown (2026-10-18 unless stated).

## 1. Which actor

| The user wants | Use | Not for |
|---|---|---|
| LATAM Get on Board tech jobs with monthly USD salary, full descriptions, company profiles and persistent only-new feeds | `data_daemon/getonbrd-jobs-scraper` | Candidate profiles; worldwide remote eligibility inferred from the remote flag; annual or original local-currency salary |
| Public Welcome to the Jungle jobs: France-focused board, including its postings abroad; full descriptions, public company metadata, contract/remote filters and only-new feeds | `data_daemon/welcome-to-the-jungle-jobs-scraper` | Separate Otta/US/UK personalized matching inventory; normalized salary benchmarks (raw source units vary); more than 1,000 hits per source search |
| Indian management, MBA, finance, consulting, CA/CFA, sales, HR, senior roles; salary bands (when disclosed); applicant counts; who is hiring in India | `data_daemon/iimjobs-jobs-scraper` | Tech roles (use Hirist); Naukri/LinkedIn/Indeed (not covered) |
| Indian software, data, DevOps, product-tech roles; skills demand; tech salary bands | `data_daemon/hirist-jobs-scraper` | Non-tech roles (use IIMJobs) |
| Indian jobs across every function and level on foundit.in (Monster India): freshers, sales, BPO, nursing, accounting, operations, IT; applicant and view counts; employer vs staffing agency; apply links to employer career sites | `data_daemon/foundit-jobs-scraper` | Naukri/LinkedIn/Indeed (not covered); senior management and MBA roles (IIMJobs has deeper coverage) |
| Indian tech jobs at product companies and startups on Instahyre (engineering, data, DevOps, product, design); company headcount, founding year and size band; work-from-home roles; hiring by company or company size | `data_daemon/instahyre-jobs-scraper` | Non-tech roles (IIMJobs, Foundit); salary bands (Instahyre does not publish pay); applicant counts (Hirist, IIMJobs) |
| Every open job of one employer whose careers page is on Oracle Recruiting Cloud / Fusion HCM (`*.oraclecloud.com/hcmUI/CandidateExperience/...`): JPMorgan Chase, Marriott, Oracle, Kotak, DTCC and thousands more | `data_daemon/oracle-hcm-jobs-scraper` | Workday, Taleo, Greenhouse, Lever, SuccessFactors sites |
| Indian IPOs: live grey market premium (GMP), QIB/NII/retail subscription, open/close/listing dates, mainboard vs SME, full IPO detail pages | `data_daemon/india-ipo-tracker` | Non-Indian IPOs; secondary-market prices (use Tickertape) |
| NSE/BSE listed companies: index constituents (NIFTY 50/100/500, NIFTY BANK, SENSEX), ratio screener, full fundamentals profile per stock | `data_daemon/tickertape-stocks-scraper` | Intraday tick data; derivatives; mutual fund NAVs |
| Dubai real-estate transactions from the official DLD register: sales (incl. off-plan), mortgages, gifts, with AED value, size and price per sqm | `data_daemon/dubai-property-transactions` | Listings/asking prices; rental contracts; other emirates |
| UK corporate insolvency notices from The Gazette: winding-up petitions (incl. HMRC), orders, administrations, liquidations, creditor meetings, with company number, addresses and insolvency practitioner | `data_daemon/uk-gazette-insolvency-notices` | Companies House filings; Scottish/Irish court records outside The Gazette |
| Upcoming Luma (lu.ma) events by city, category, keyword or organiser calendar: dates, venue, GPS, ticket prices, guest count, hosts with social handles | `data_daemon/luma-events-scraper` | Eventbrite, Meetup (not covered); attendee or guest lists (never collected) |

## 2. How to call any of them

Authentication: header `Authorization: Bearer <APIFY_TOKEN>` (token at https://console.apify.com/settings/integrations). In URLs write the actor as `data_daemon~<name>` or use the hex id.

```bash
# synchronous: start, wait (max 300 s), get the records back as JSON (or &format=csv / xlsx; &fields=a,b.c to pick columns)
curl -sS -X POST "https://api.apify.com/v2/acts/data_daemon~iimjobs-jobs-scraper/run-sync-get-dataset-items?clean=1" \
  -H "Authorization: Bearer $APIFY_TOKEN" -H "Content-Type: application/json" \
  -d '{"queries":["product manager"],"postedWithinDays":7,"maxJobsPerQuery":50}'

# asynchronous (for runs that may exceed 300 s): start, poll, read
curl -sS -X POST "https://api.apify.com/v2/acts/data_daemon~oracle-hcm-jobs-scraper/runs" -H "Authorization: Bearer $APIFY_TOKEN" -H "Content-Type: application/json" -d '{...}'   # -> data.id
curl -sS "https://api.apify.com/v2/actor-runs/{runId}" -H "Authorization: Bearer $APIFY_TOKEN"                                 # -> data.status, data.defaultDatasetId
curl -sS "https://api.apify.com/v2/datasets/{datasetId}/items?clean=1&limit=1000&offset=0" -H "Authorization: Bearer $APIFY_TOKEN"

# live input schema of the deployed build (field names, enums, defaults) - read this before building an input
curl -sS "https://api.apify.com/v2/acts/data_daemon~iimjobs-jobs-scraper/builds/default" -H "Authorization: Bearer $APIFY_TOKEN"   # -> data.inputSchema (JSON string)
```

Other routes: Apify MCP server `https://mcp.apify.com?tools=data_daemon/iimjobs-jobs-scraper,data_daemon/india-ipo-tracker` (comma-separate any of the names above; Bearer header or OAuth; tools `search-actors`, `fetch-actor-details`, `call-actor` are also available), Apify CLI `apify call data_daemon/<name> -i '<json>'`, SDKs `apify-client` (Python, Node). Ready scripts: [`examples/run-sync/`](examples/run-sync/), [`examples/only-new-jobs/`](examples/only-new-jobs/).

Rules of thumb:
- **Size the cost first**: records x price per event. Cap with `maxJobs`, `maxJobsPerSite`, `maxItems`, `maxEvents`. Tell the user the estimate when it is above about $1.
- **Turn off detail fetching when the user only needs counts or titles** (`includeDescription`, `includeDetails`, `includeLinkedData`, `includeIpoDetails` are on by default on the actors that have them and double the per-record price on IIMJobs, Hirist, Oracle and Gazette; on Foundit, Instahyre and Luma they only change speed, not price).
- **Daily feeds**: for IIMJobs/Hirist/Foundit/Instahyre set `postedWithinDays: 1` (on Instahyre the date is checked per job page, so prefer `onlyNewSinceLastRun` there) and, if the live schema has it, `onlyNewSinceLastRun: true` (actor-side memory per search, skipped jobs not charged; `stateName` names the search) or `skipJobIds: [...]`. Luma has the same `onlyNewSinceLastRun` / `stateName` plus `skipEventIds`. Always de-duplicate on `id` client-side too.
- **Never fill gaps**: salaries are hidden on most Indian postings (`salaryHidden: true`); report the count of disclosed salaries next to any statistic.
- **Run-sync limit**: 300 s. Full-board exports and big Oracle tenants (JPMC has 7,000+ open jobs) need the async pattern.

## 3. Actor catalog

### 3.1 IIMJobs Jobs Scraper - `data_daemon/iimjobs-jobs-scraper` (`fEBnL9mUQr81TGuh4`)

https://apify.com/data_daemon/iimjobs-jobs-scraper - IIMJobs.com, India's board for MBA, finance, consulting, CA/CFA, sales, HR and senior management roles.

Use when: Indian non-tech hiring data; salary (LPA) where disclosed; applicant counts per posting; company hiring signals with AmbitionBox rating; a daily feed of new management roles.

Input (verified: `{"queries":["product manager"],"postedWithinDays":7,"maxJobsPerQuery":3}` → 3 jobs):

```json
{
  "queries": ["product manager", "investment banking"],
  "locations": ["Bangalore", "Mumbai"],
  "minExperience": 5,
  "maxExperience": 12,
  "postedWithinDays": 7,
  "includeDescription": true,
  "maxJobsPerQuery": 100,
  "maxJobs": 0
}
```

| Field | Notes |
|---|---|
| `queries` string[] | one search per keyword; results de-duplicated across keywords |
| `locations` string[] | city filter matched against the job's listed cities: `Bangalore`, `Mumbai`, `Delhi NCR`, `Gurgaon`, `Pune`, `Hyderabad`, `Chennai`, `Remote`, `Anywhere in India` |
| `minExperience` / `maxExperience` int | years; overlap with the posting's range |
| `postedWithinDays` int | 1, 3, 7, 15, 30; omit for all |
| `includeDescription` bool (default true) | full JD text + HTML and company profile; +$0.002 per job |
| `maxJobsPerQuery` int (default 40), `maxJobs` int (0 = no cap) | cost caps |
| `onlyNewSinceLastRun` bool, `stateName` string, `skipJobIds` array | monitor mode and explicit exclusions; read the live schema |

Output, one record per job: `id`, `site`, `url`, `title`, `designation`, `company` {`name`, `domain`, `logo`, `confidential`, `ambitionBoxRating`, `ambitionBoxReviews`, `ambitionBoxUrl`, `about`}, `recruiter` {`designation`; `name` only where the board shows it publicly, otherwise masked}, `experienceMinYears`, `experienceMaxYears`, `salaryMinLpa`, `salaryMaxLpa`, `salaryHidden`, `locations` [], `remote`, `skills` [], `mandatorySkills` [], `applicants`, `postedAt` (ISO), `description`, `descriptionHtml` (with `includeDescription`), `query`, `scrapedAt`.

Cost: `job` $0.002 + `job-description` $0.002 → $4 per 1,000 jobs with descriptions, $2 without.

### 3.2 Hirist.tech Jobs Scraper - `data_daemon/hirist-jobs-scraper` (`z2fAtS4KgvaqkK85b`)

https://apify.com/data_daemon/hirist-jobs-scraper - Hirist.tech (hirist.com), India's tech-only board (same publisher as IIMJobs). **Identical input and output schema to 3.1**; the only difference is the board.

Use when: Indian software/data/DevOps/product-tech roles; skills demand (tagged `skills` and `mandatorySkills` per posting); tech salary bands where disclosed; a daily feed of new tech roles.

Input (verified: `{"queries":["python developer"],"postedWithinDays":7,"maxJobsPerQuery":3}` → 3 jobs):

```json
{ "queries": ["data engineer", "python developer"], "locations": ["Bangalore", "Remote"], "postedWithinDays": 1, "includeDescription": false, "maxJobsPerQuery": 200 }
```

Output and cost: as 3.1 (`job` $0.002 + `job-description` $0.002).

### 3.3 Oracle HCM / Recruiting Cloud Jobs Scraper - `data_daemon/oracle-hcm-jobs-scraper` (`ADeJJ5VJCcUqYI87X`)

https://apify.com/data_daemon/oracle-hcm-jobs-scraper - every requisition on any Oracle Recruiting Cloud (Oracle Fusion Cloud HCM) career site.

Use when: the user names an employer whose careers page URL contains `oraclecloud.com/hcmUI/CandidateExperience`; counting an employer's open roles by location/category; monitoring a large employer's new postings; building a jobs feed from enterprise career sites. To find a company's site, web-search `site:oraclecloud.com CandidateExperience "<company>"`. Known sites: Oracle `https://eeho.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_45001/requisitions`, JPMorgan Chase `https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions`, Marriott `https://ejwl.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX/requisitions`, Kotak Mahindra Bank `https://hcbt.fa.em2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX/requisitions`, DTCC `https://ebxr.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/requisitions`.

Input (verified: Oracle CX_45001 with `"keyword":"engineer","maxJobsPerSite":3` → 3 jobs):

```json
{
  "careerSiteUrls": ["https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions"],
  "keyword": "software engineer",
  "location": "India",
  "postedWithinDays": 7,
  "workplaceTypes": ["ORA_REMOTE", "ORA_HYBRID"],
  "includeDetails": true,
  "maxJobsPerSite": 500,
  "maxJobs": 0
}
```

| Field | Notes |
|---|---|
| `careerSiteUrls` string[] (required) | any page of the site works, including a single job URL |
| `keyword` string | omit to list every open requisition |
| `location` string | as typed on the site, e.g. `India`, `London`, `Texas, United States` |
| `postedWithinDays` int | Oracle supports exactly 7 or 30 (other values round up) |
| `workplaceTypes` string[] | `ORA_REMOTE`, `ORA_HYBRID`, `ORA_ON_SITE` |
| `includeDetails` bool (default true) | full description, qualifications, responsibilities, flex fields; +$0.002 per job |
| `maxJobsPerSite` int (default 50; 0 = all), `maxJobs` int | cost caps |

Output, one record per requisition: `id`, `title`, `url`, `applyUrl`, `tenantHost`, `careerSite` {`origin`, `siteNumber`, `name`}, `postedDate`, `externalPostedStartDate`, `language`, `primaryLocation`, `country`, `locations` [], `remote`, `workplaceType`, `jobFunction`, `category`, `hotJob`, `trending`, `shortDescription`, and with `includeDetails`: `description`, `descriptionHtml`, `qualifications`, `responsibilities`, `corporateDescription`, `skills` [], `flexFields` {employer-defined, e.g. `Role`, `Job Type`}; plus `scrapedAt`. The employer name is `careerSite.name`.

Cost: `job` $0.002 + `job-details` $0.002.

### 3.4 India IPO Tracker - `data_daemon/india-ipo-tracker` (`Q8tYzzX5YLgPLbQu4`)

https://apify.com/data_daemon/india-ipo-tracker - current and upcoming Indian IPOs, live grey market premium, live subscription, calendar, optional detail pages (sources: Chittorgarh, InvestorGain).

Use when: "what IPOs are open / upcoming in India", "GMP of X", "how many times is X subscribed (QIB/NII/retail)", IPO calendars and alert bots, mainboard vs SME.

Input (verified: `{"reports":["gmp"],"maxItems":5}` → 5 rows):

```json
{ "reports": ["currentIpos", "gmp", "subscription", "calendar"], "category": "all", "includeIpoDetails": false, "maxItems": 0 }
```

| Field | Notes |
|---|---|
| `reports` string[] | `currentIpos` (status, price band, lot, dates), `gmp` (live grey market premium), `subscription` (QIB/NII/retail multiples), `calendar` (events). Other values exist in the schema (`ipoList`, `gmpPerformance`, `listingPerformance`); check the actor page before relying on them. |
| `category` | `all`, `mainboard`, `sme` |
| `includeIpoDetails` bool (default false) | one `ipoDetail` record per IPO: price band, lot size, timetable, reservation, anchors, financials, objects; $0.015 each |
| `financialYear` string | e.g. `2025-26`, for list reports |
| `maxItems` int | 0 = no limit |

Output, one record per report row with `reportType` set: common `ipoName`, `slug`, `url`, `category` (Mainboard/SME), `status`, `openDate`, `closeDate`, `listingDate`, `issuePrice`, `issueSizeCr`, `lotSize`, `scrapedAt`; `gmp` rows add `gmp`, `gmpPercent`, `gmpText`, `rating`, `subscriptionText`, `priceToEarnings`, `allotmentDate`, `anchorInvestors`, `updatedOn`; `subscription` rows add `qibX`, `niiX`, `sNiiX`, `bNiiX`, `retailX`, `totalX`, `applications`, `subscriptionAsOn`. Every row also carries `fields` (all source columns, cleaned) and `meta` (hidden machine columns such as ISIN/symbol).

Cost: `report-row` $0.003; `ipo-detail` $0.015.

### 3.5 Tickertape India Stocks Scraper - `data_daemon/tickertape-stocks-scraper` (`LjrpONBpsSkqWrHs5`)

https://apify.com/data_daemon/tickertape-stocks-scraper - NSE/BSE listed companies via Tickertape: index constituents, a ratio screener, and full fundamentals profiles.

Use when: "list of NIFTY 50 / NIFTY BANK / NIFTY 500 stocks with price and sector", "screen Indian stocks by market cap / PE / dividend yield / ROE", "fundamentals, shareholding history and 10-year financials of RELIANCE".

Input (verified: `{"mode":"index","indexSid":"NIFTY 50","maxItems":5}` → 5 rows; `{"mode":"screener","screenerMatch":{"mrktCapf":{"g":50000}},"maxItems":5}` → 5 rows):

```json
{ "mode": "index", "indexSid": "NIFTY 50" }
{ "mode": "screener", "screenerMatch": { "mrktCapf": { "g": 10000 }, "apef": { "l": 25 }, "divYield": { "g": 1 } }, "screenerSortBy": "mrktCapf", "screenerSortDesc": true, "maxItems": 200 }
{ "mode": "stocks", "stocks": ["RELIANCE", "TCS", "HDFCBANK"], "fullProfile": true }
```

| Field | Notes |
|---|---|
| `mode` | `index`, `screener`, `stocks` |
| `indexSid` | `NIFTY 50`, `NIFTY 100`, `NIFTY 500`, `NIFTY BANK`, `SENSEX`, or Tickertape ids like `.NSEI`, `.NSEBANK` |
| `screenerMatch` object | Tickertape filter: `mrktCapf` (market cap, Cr), `apef` (PE), `pbr` (PB), `divYield`, `roe`, `pr1y` ... with `g` (greater) / `l` (less) |
| `screenerFields` string[] | extra ratio columns on top of the defaults |
| `stocks` string[] | NSE tickers, company names or Tickertape URLs (profile mode) |
| `maxItems` int | 0 = no limit |

Output: index rows `indexSid`, `sid`, `ticker`, `name`, `sector`, `lastPrice`, `change1dPct`, `freeFloatPct`, `url`, `scrapedAt`; screener rows `sid`, `ticker`, `name`, `sector`, `subindustry`, `lastPrice`, `mrktCapf`, `apef`, `pbr`, `divYield`, `roe`, `beta`, `pr1w`, `4wpct`, `url`, `scrapedAt` (+ requested `screenerFields`); stock profiles `ticker`, `name`, `sector`, `industry`, `isin`, `quote`, `marketCapCr`, `pe`, `pb`, `dividendYield`, `roe`, `week52High`, `week52Low`, `scorecard`, `shareholding` (quarterly promoter/FII/DII/MF/retail), `incomeStatementAnnual`, `balanceSheetAnnual`, `cashFlowAnnual`, `incomeStatementQuarterly`, `analystForecast`, `dividends`, `corporateActions`, `mutualFundHoldings`, `peers`, `investmentChecklist`.

Cost: `quote-row` $0.002 (index and screener rows); `stock-profile` $0.02.

### 3.6 Dubai DLD Property Transactions - `data_daemon/dubai-property-transactions` (`fSoMCyHMdU0YHp4kk`)

https://apify.com/data_daemon/dubai-property-transactions - registered transactions from the Dubai Land Department open-data register.

Use when: sold prices and price per sqm by area/project; off-plan vs ready sales volumes; mortgage registrations; weekly market stats for Dubai; comps for a valuation.

Input (verified: `{"transactionGroup":"sales","maxItems":3}` → 3 rows; dates default to the last 7 days):

```json
{ "fromDate": "2026-10-01", "toDate": "2026-10-07", "transactionGroup": "sales", "offPlan": "all", "usage": "residential", "propertyType": "unit", "maxItems": 2000 }
```

| Field | Notes |
|---|---|
| `fromDate` / `toDate` `YYYY-MM-DD` | default: 7 days ago → today |
| `transactionGroup` | `all`, `sales`, `mortgages`, `gifts` |
| `offPlan` | `all`, `offplan`, `ready` |
| `freehold` | `all`, `freehold`, `nonfreehold` |
| `usage` | `all`, `residential`, `commercial` |
| `propertyType` | `all`, `unit`, `building`, `land` |
| `areaId` string | one DLD area id (each row carries its `areaId`) |
| `includeArabic` bool | adds Arabic names |
| `maxItems` int (default 200; 0 = all in range) | a busy week has 5,000+ sales |

Output, one record per transaction: `transactionNumber`, `transactionDate`, `transactionDateTime`, `group`, `groupId`, `procedure` (e.g. `Sell`, `Sell - Pre registration`, `Mortgage Registration`), `procedureId`, `usage`, `offPlan`, `freehold`, `area`, `areaId`, `project`, `masterProject`, `propertyType`, `propertySubType`, `rooms`, `parking`, `buildingAge`, `parcelId`, `propertyId`, `transactionValueAed`, `procedureAreaSqm`, `actualAreaSqm`, `pricePerSqmAed`, `nearestMetro`, `nearestMall`, `nearestLandmark`, `totalSellers`, `totalBuyers`, `source`, `scrapedAt`.

Cost: `transaction` $0.001 ($1 per 1,000).

### 3.7 UK Gazette Insolvency Notices - `data_daemon/uk-gazette-insolvency-notices` (`4We8IBpLtJp6OkQd8`)

https://apify.com/data_daemon/uk-gazette-insolvency-notices - official UK insolvency notices from The Gazette (Open Government Licence).

Use when: lists of companies facing winding-up petitions (incl. HMRC petitions), winding-up orders, administrations, liquidations, creditor meetings; credit-risk and supplier monitoring; insolvency practitioner leads.

Input (verified: `{"noticeTypes":["2450"],"maxItems":3,"includeLinkedData":true}` → 3 rows):

```json
{ "service": "insolvency", "noticeTypes": ["2450", "2452", "2410"], "startPublishDate": "2026-10-01", "text": "", "sortBy": "latest-date", "includeLinkedData": true, "maxItems": 200 }
```

| Field | Notes |
|---|---|
| `service` | `insolvency` (default), `companies`, `all-notices`, `wills-and-probate` |
| `noticeTypes` string[] | Gazette codes: `2450` petitions to wind up, `2451` partnership winding-up petitions, `2452` winding-up orders, `2441` resolutions for winding up, `2432`/`2443` appointment of liquidators, `2410` administration appointments, `2442` meetings of creditors, `2433` notices to creditors; omit for all types in the service |
| `categoryCode` string | e.g. `G205000000` corporate insolvency, `G206000000` personal insolvency |
| `text` string | free text: company name, practitioner, town |
| `startPublishDate` / `endPublishDate` `YYYY-MM-DD` | publication window |
| `includeLinkedData` bool (default true) | adds the structured record (company number, addresses, court case, practitioners); +$0.003 per notice |
| `maxItems` int (default 40) | cost cap |

Output, one record per notice: `noticeId`, `url`, `title`, `category`, `categories`, `noticeCode`, `noticeTypes`, `published`, `updated`, `publisher`, `status`, `summary`, `contentHtml`, `source`, `scrapedAt`; with `includeLinkedData`: `companyName`, `companyNumber`, `companyTypes`, `registeredOffice`, `principalTradingAddress`, `subjectType`, `dateOfHearing`, `dateOfPetitionPresentation`, `dateToRequestAppearance`, `practitioners` [{`name`, `type`, `firm`, `email`, `telephone`, `address`}], and the full `linkedData` object (petitioner under `linkedData.petitioner`, court and case under `linkedData.hasCourtCase.hasCourt.courtName` / `linkedData.hasCourtCase.caseCode`).

Cost: `notice` $0.002 + `notice-details` $0.003.

### 3.8 Foundit (Monster India) Jobs Scraper - `data_daemon/foundit-jobs-scraper` (`UdAJvB5H72gNbfQfM`)

https://apify.com/data_daemon/foundit-jobs-scraper - foundit.in (formerly Monster India), a general Indian job board across all functions and levels, including many postings syndicated from employers' own career sites.

Use when: Indian jobs outside the MBA and tech niches (sales, BPO, nursing, accounting, operations, freshers); fresher filters by experience band; applicant and view counts; employer vs staffing agency (`company.employerType`); the employer's own apply link for syndicated postings.

Input (verified 2026-10-21: `{"queries":["data analyst"],"locations":["Bangalore"],"postedWithinDays":7,"maxJobsPerQuery":5}` → 5 jobs with descriptions in 8 s):

```json
{
  "queries": ["data analyst", "sales manager"],
  "locations": ["Bangalore", "Mumbai"],
  "minExperience": 0,
  "maxExperience": 3,
  "postedWithinDays": 7,
  "jobTypes": ["Permanent Job"],
  "includeDescription": true,
  "sort": "newest",
  "maxJobsPerQuery": 100,
  "maxJobs": 0
}
```

| Field | Notes |
|---|---|
| `queries` string[] (required) | one search per keyword; a job found by two keywords is saved and charged once |
| `locations` string[] | `Bangalore`, `Mumbai`, `Delhi` (covers Gurugram and Noida), `Hyderabad`, `Chennai`, `Pune`, `Kolkata`, `Ahmedabad`, `Remote`; empty = all of India |
| `minExperience` / `maxExperience` int | years, 0-30; `maxExperience: 1` is a fresher filter; `minExperience` of 1 or more also drops jobs without a stated range |
| `postedWithinDays` int | 1-365 |
| `jobTypes` string[] | `Permanent Job`, `Contract Job`, `Work From Home`, `Internship`, `Temporary` |
| `minSalaryLpa` / `maxSalaryLpa` int | disclosed annual salary in lakh INR; most postings do not disclose pay and are excluded when either is set |
| `includeDescription` bool (default true) | full JD, company profile, skill tags, view count, coordinates; **same price either way**, about twice as fast when off |
| `sort` | `newest` (default) or `relevance` |
| `maxJobsPerQuery` int (default 50), `maxJobs` int (0 = no cap) | cost caps |
| `onlyNewSinceLastRun` bool, `stateName` string, `skipJobIds` string[] | monitor mode (actor-side memory per search in your account, skipped jobs not charged) and explicit exclusions |

Output, one record per job: `id` (number), `dedupKey` (`foundit:<id>`), `url`, `applyUrl` (the employer's site for syndicated jobs), `title`, `company` {`id`, `name` (null when `confidential`), `logo`, `url`, `employerType` (`company` or `consultant`), `about`, `greatPlaceToWork`}, `locations` [], `locationDetails` [{`city`, `state`, `country`, `lat`, `lon`}], `remote`, `experienceMinYears`, `experienceMaxYears`, `salaryMinInr`, `salaryMaxInr`, `salaryMinLpa`, `salaryMaxLpa`, `salaryCurrency`, `salaryHidden`, `jobTypes` [], `employmentTypes` [], `industries` [], `functions` [], `designations` [], `skills` [], `applicants`, `views`, `postedAt`, `createdAt`, `updatedAt`, `closesAt`, `isActive`, `syndicated`, `urgentlyHiring`, `description`, `descriptionHtml`, `query`, `scrapedAt`. Recruiter names and phone numbers are not output.

Cost: `job` $0.0008 with the description included → $0.80 per 1,000 jobs, plus one `apify-actor-start` event of $0.001 per run (FREE-tier list prices).

### 3.9 Luma Events Scraper - `data_daemon/luma-events-scraper` (`51GnTTp3L9zzrKcb7`)

https://apify.com/data_daemon/luma-events-scraper - upcoming public events on Luma (lu.ma / luma.com) from city feeds, categories, keyword search, organiser calendars or event URLs.

Use when: "which AI or tech events are in London this month"; event calendars and newsletters; finding organisers and hosts with their website and social handles; ticket prices, capacity and sold-out status; monitoring an organiser's calendar for new events.

Input (verified 2026-10-21: `{"cities":["London"],"categories":["ai"],"daysAhead":30,"maxEvents":5}` → 5 events with details in 5 s):

```json
{
  "cities": ["London"],
  "categories": ["ai", "tech"],
  "daysAhead": 30,
  "priceType": "any",
  "eventFormat": "any",
  "includeDetails": true,
  "maxEvents": 100,
  "maxEventsPerSource": 0
}
```

| Field | Notes |
|---|---|
| `cities` string[] (required, default `["San Francisco"]`) | Luma discover cities (87), e.g. `San Francisco`, `New York`, `London`, `Berlin`, `Bengaluru`, `Tokyo`, `Singapore`; a `lu.ma/<city>` URL or `discplace-...` id also works; `[]` with `query` searches worldwide |
| `categories` string[] | `ai`, `tech`, `arts`, `climate`, `crypto`, `fitness`, `wellness`, `running`, `books`, `games`, `family`, `fooddrink`; applied around each city |
| `query` string | keyword matched by Luma in names and descriptions (50 best matches per feed) |
| `startUrls` string[] | organiser calendars (`https://lu.ma/planetscale`), single events, city or category pages, or `cal-` / `evt-` / `discplace-` ids; when only URLs are given the default city is not scraped |
| `daysAhead` int, `startDateFrom` / `startDateTo` `YYYY-MM-DD` | date window; feeds are ordered by start date, so `maxEvents` takes the soonest |
| `priceType` | `any`, `free`, `paid` |
| `eventFormat` | `any`, `in-person`, `online` |
| `includeDetails` bool (default true) | description, ticket types, categories, sold-out flag; **same price either way** |
| `maxEvents` int (default 25), `maxEventsPerSource` int (0 = no cap) | cost caps; a city has 50-150 upcoming events |
| `onlyNewSinceLastRun` bool, `stateName` string, `skipEventIds` string[] | monitor mode and explicit exclusions |

Output, one record per event: `id` (`evt-...`), `dedupKey`, `url`, `name`, `startAt`, `endAt` (UTC), `timezone`, `startAtLocal`, `endAtLocal`, `format` (`in-person` or `online`), `venue`, `address`, `city`, `region`, `country`, `countryCode`, `lat`, `lng`, `addressHidden` (venue shown only to registered guests: `venue` and `address` are null and coordinates are rounded to about 1 km), `isFree`, `price`, `maxPrice`, `currency`, `soldOut`, `spotsRemaining`, `nearCapacity`, `requireApproval`, `registration`, `waitlist`, `guestCount`, `eventType`, `seriesId`, `visibility`, `discoverCity`, `calendar` {`id`, `name`, `slug`, `url`, `description`, `avatarUrl`, `website`, `isVerified`, `isPersonal`, `twitter`, `instagram`, `linkedin`, `youtube`, `tiktok`, `city`, `country`}, `hosts` [{`id`, `name`, `bio`, `username`, `profileUrl`, `avatarUrl`, `website`, `linkedin`, `twitter`, `instagram`, `tiktok`, `youtube`, `isVerified`}], `hostNames` [], `categories` [], `coverUrl`, with `includeDetails`: `description`, `descriptionHtml`, `ticketTypes` [{`id`, `name`, `isFree`, `price`, `currency`, `description`, `capacity`, `spotsRemaining`, `requireApproval`, `validFrom`, `validUntil`}]; plus `source` {`type`, `name`} and `scrapedAt`. Guest lists, attendee names, e-mails and phone numbers are never collected.

Cost: `event` $0.0015 with details included → $1.50 per 1,000 events, plus one `apify-actor-start` event of $0.001 per run (FREE-tier list prices).

### 3.10 Instahyre Jobs Scraper - `data_daemon/instahyre-jobs-scraper` (`GMe0nzJEhMj9PV8Mb`)

https://apify.com/data_daemon/instahyre-jobs-scraper - Instahyre, the hiring platform Indian product companies and startups use for engineering, data, product and design roles (about 12,700 open jobs on 2026-10-21; 6,800 in Bangalore, 1,100 work-from-home).

Use when: Indian tech jobs with the hiring company's headcount, founding year, tagline and website; filtering by company size (`small` < 100, `medium` 100-1,000, `large` > 1,000) or by company; work-from-home tech roles; startup hiring signals for B2B sales.

Input (verified 2026-10-21: `{"queries":["python"],"locations":["Bangalore"],"maxJobsPerQuery":5}` → 5 jobs with descriptions in 6 s; the `{}` default returned 50 jobs in 20 s):

```json
{
  "queries": ["python", "golang"],
  "locations": ["Bangalore", "Work From Home"],
  "companySizes": ["small", "medium"],
  "minExperience": 2,
  "maxExperience": 6,
  "postedWithinDays": 30,
  "includeDescription": true,
  "maxJobsPerQuery": 50,
  "maxJobs": 0
}
```

| Field | Notes |
|---|---|
| `queries` string[] (required) | skills or roles, matched against titles and skill tags (broad: `data science` also returns data-engineering roles); `skills` is accepted as an alias |
| `locations` string[] | the site's own names: `Bangalore`, `Mumbai`, `Delhi`, `Gurgaon`, `Noida`, `Hyderabad`, `Chennai`, `Pune`, `Kolkata`, `Ahmedabad`, `Work From Home`, regions (`South India`) and ~300 smaller cities; `Bengaluru`/`Gurugram`/`Remote` are mapped; unknown names are dropped and named in the status message |
| `companySizes` string[] | `small`, `medium`, `large`; applied by the site |
| `companies` string[] | company names; with `queries: []` this lists everything a company posts |
| `jobType` | `all` (default), `full-time`, `internship` |
| `experienceYears` int | the site's own filter: jobs whose range covers this many years; cheapest way to narrow |
| `minExperience` / `maxExperience` int | overlap band, read from each job page; jobs without a stated range are kept |
| `postedWithinDays` int | 1-365; the site has no date filter, so the date is read from each job page and older jobs are left out unpaid |
| `includeDescription` bool (default true) | fetches the job page: description, posting date, experience range, employment type, functions, company website; **same price either way**, about three times as fast when off |
| `maxJobsPerQuery` int (default 50), `maxJobs` int (0 = no cap) | cost caps; the site serves 35 jobs per page |
| `onlyNewSinceLastRun` bool, `stateName` string, `skipJobIds` string[] | monitor mode (actor-side memory per search in your account, skipped jobs not charged) and explicit exclusions |

Output, one record per job: `id` (number), `dedupKey` (`instahyre:<id>`), `url`, `applyUrl` (same page), `title`, `company` {`id`, `name`, `tagline`, `about`, `founded`, `employeeCount`, `size`, `logo`, `website`, `featured`, `diversityEmployer`}, `locations` [], `remote`, `acceptsOutstation`, `experienceMinYears`, `experienceMaxYears`, `employmentType` (`FULL_TIME` / `INTERN`), `skills` [], `functions` [], `postedAt` (day precision), `description`, `descriptionHtml`, `query`, `scrapedAt`. No salary or applicant counts (the site does not publish them); recruiter names are not output.

Cost: `job` $0.0008 with the description included → $0.80 per 1,000 jobs, plus one `apify-actor-start` event of $0.001 per run (FREE-tier list prices).

### 3.11 Welcome to the Jungle Jobs Scraper - `data_daemon/welcome-to-the-jungle-jobs-scraper` (`rJLnujVhP6ucdnrof`)

https://apify.com/data_daemon/welcome-to-the-jungle-jobs-scraper - the France-focused public WTTJ board, including its postings abroad. Does not cover the separate Otta/US/UK personalized matching inventory.

Use when: public WTTJ jobs as JSON, full descriptions and public company profiles; keyword/country/contract/remote filters; a persistent feed of jobs not delivered before.

```json
{"queries":["python"],"countryCodes":["FR"],"contractTypes":["FULL_TIME"],"maxJobs":20}
```

Empty input searches Python and delivers up to 20 jobs. `maxJobsPerQuery` and `maxJobs` default to 20. A source search exposes at most 1,000 accessible hits; narrow broad searches with country/company/contract/language/remote filters. `locations` (office substring) and `postedWithinDays` (unknown dates excluded) are local filters within that source window.

Input: `queries`, `countryCodes`, `locations`, `contractTypes`, `remoteModes` (`fulltime`, `partial`, `punctual`, `no`, `unknown`), `languages`, `companySlugs`, `salaryCurrency`, `postedWithinDays`, `includeDescription` (true), `maxJobsPerQuery`, `maxJobs`, `skipJobIds`, `onlyNewSinceLastRun`, `stateName`.

Only-new memory remembers delivered IDs for 120 days, at most 50,000 per feed. Same named feed shares state across tasks in the account; avoid overlapping runs. Later runs may fill older unseen backlog left by the first run's cap. Output `id`, `sourceId` or `dedupKey` can be used in `skipJobIds`.

Output: stable `id`, `sourceId`, `dedupKey`, `url`, `applyUrl`, `title`, `company`, `locations`, `offices`, `countryCodes`, `remoteMode`, `contractType`, `language`, `salary`, experience/education labels, `profession`, `sectors`, `skills`, `postedAt`, `updatedAt`, `startDate`, full description HTML/text, candidate profile and recruitment process, `query`, `source`, `scrapedAt`. **Salary numbers have inconsistent employer-entered units; preserve them as provided and never guess a multiplier for benchmarking.**

Cost: $0.0008 per delivered job with description included plus $0.001 per run at Free/Starter rates. Skipped/duplicate jobs are not charged. Scale job/start $0.00068/$0.00085; Business+ $0.00056/$0.0007.

### 3.12 Get on Board Jobs Scraper — `data_daemon/getonbrd-jobs-scraper` (`S9jm2Eykh93efOMpg`)

https://apify.com/data_daemon/getonbrd-jobs-scraper — public LATAM tech jobs. `{}` enumerates all 18 categories and returns up to 50 jobs. Results are source ordered within categories, not globally newest first.

Input: `categories` (source slugs), `keywords` (local OR match on title/tags/description), `remoteModalities` (`fully_remote`, `remote_local`, `hybrid`, `no_remote`), `remoteOnly`, `seniorities`, `countries` (source eligibility; names/common ISO codes), `minSalaryUsd` (minimum lower bound, USD/month), `withSalaryOnly`, `postedWithinDays`, `maxItems` (1–10,000, default 50), `onlyNew`, `stateName`, `skipIds`.

Example: `{"categories":["programming"],"remoteOnly":true,"minSalaryUsd":1000,"maxItems":20}`.

Only-new mode retains successfully delivered IDs in named `getonbrd-jobs-state` KVS, scoped by normalized filters plus `stateName`. Cap changes preserve memory; filter changes use separate state. No expiry. Avoid overlapping same-feed runs. Skipped/filtered rows are not charged or marked delivered. Capped runs may leave older unseen backlog.

Output: `id`, `url`, `title`, `company` (id/name/url/website/logo/description/country), `category`, `categoryId`, `tags`, `seniority`, `seniorityCode`, `employmentType`, `modality`, `remote`, `remoteZone`, `countries`, `cities`, `salary` (min/max/currency USD/period month), `description`, `descriptionHtml`, `publishedAt`, `applicationCount`, `source`, `scrapedAt`.

Price: job/start FREE and BRONZE $0.0008/$0.001; SILVER $0.00068/$0.00085; GOLD+ $0.00056/$0.0007. Full description/company included. Repeated IDs skipped without a job charge; an empty repeat still incurs the start fee.

## 4. Not covered (do not route here)

Naukri, LinkedIn, Indeed, Glassdoor; Workday/Taleo/Greenhouse/Lever career sites; Indian equity price history or F&O; mutual funds; Dubai rental contracts or listings; Companies House filings; Eventbrite, Meetup or any event's attendee list. Startup India / DPIIT directory data: the `data_daemon/startup-india-dpiit-scraper` actor is currently private while its source API is down; do not call it.

## 5. Examples in this repository

`python/<actor>.py` and `node/<actor>.mjs` (apify-client SDK), `examples/run-sync/` (plain REST, sync and async, stdlib/no-deps), `examples/only-new-jobs/` (scheduled de-duplicated jobs feed), `n8n/` (schedule → HTTP → Google Sheets/Slack workflows), `skills/daemon-data-apify-actors/SKILL.md` (this catalog as an agent skill).