[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-apify-apify-financial-news":3,"mdc-8dfa5d-key":34,"related-org-apify-apify-financial-news":2304,"related-repo-apify-apify-financial-news":2452},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":23,"repoUrl":24,"updatedAt":25,"license":26,"forks":27,"topics":28,"repo":29,"sourceUrl":32,"mdContent":33},"apify-financial-news","extract financial news for portfolio companies","Discover and extract financial news for tracked portfolio companies across 33 verified Tier 1 sources (Bloomberg, Reuters, FT, WSJ, IntelliNews, ČTK, PAP, BTA, TASR, ING Think, ECB, EC Press Corner, ...) plus broad Google News fallback. Use when the user asks to find news about a company, get press coverage, monitor financial press, run a news scan, or check headlines for a portfolio company. Reads tracked companies from data\u002Fcompanies.json. Do NOT use for marketing\u002Fsocial-listening (use apify\u002Fawesome-skills) or for morning-briefing formatting (out of scope).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"apify","Apify","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fapify.png",[12,16,17,20],{"name":13,"slug":14,"type":15},"Research","research","tag",{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},"Finance","finance",{"name":21,"slug":22,"type":15},"Web Scraping","web-scraping",227,"https:\u002F\u002Fgithub.com\u002Fapify\u002Fawesome-skills","2026-05-23T06:06:02.858883",null,56,[],{"repoUrl":24,"stars":23,"forks":27,"topics":30,"description":31},[],"Community collection of Apify agent skills for AI coding assistants","https:\u002F\u002Fgithub.com\u002Fapify\u002Fawesome-skills\u002Ftree\u002FHEAD\u002Fskills\u002Fapify-financial-services\u002Fskills\u002Fapify-financial-news","---\nname: apify-financial-news\ndescription: Discover and extract financial news for tracked portfolio companies across 33 verified Tier 1 sources (Bloomberg, Reuters, FT, WSJ, IntelliNews, ČTK, PAP, BTA, TASR, ING Think, ECB, EC Press Corner, ...) plus broad Google News fallback. Use when the user asks to find news about a company, get press coverage, monitor financial press, run a news scan, or check headlines for a portfolio company. Reads tracked companies from data\u002Fcompanies.json. Do NOT use for marketing\u002Fsocial-listening (use apify\u002Fawesome-skills) or for morning-briefing formatting (out of scope).\nauthor: chocholous\nauthor_url: https:\u002F\u002Fgithub.com\u002Fchocholous\n---\n\n# Financial News Intelligence\n\nDiscover and extract financial news for portfolio companies via Apify Actors. Two modes:\n\n- **Single company** — news scan for one company.\n- **Portfolio scan** — same pipeline run across multiple companies.\n\n33 Tier 1 sources organized in 4 categories (Global \u002F Pan-European \u002F Institutional \u002F CEE Local). Tier 2 = broad Google News fallback for unverified domains.\n\n**Estimated cost**: $0.10–0.50 per single company, $1–5 per full portfolio scan.\n\n## Prerequisites\n\n- Apify access — preferred: `apify` CLI (`npm install -g apify-cli && apify login`); fallback: Apify MCP connector (`call-actor` tool). CLI is faster and preferred when both are available.\n- Python 3 + `pip install readability-lxml lxml` (for the `extract_and_clean.py` post-processor)\n- Companies data at `${CLAUDE_PLUGIN_ROOT}\u002Fdata\u002Fcompanies.json`\n\n`${CLAUDE_PLUGIN_ROOT}` is the plugin's root directory (where `.claude-plugin\u002F` lives). It is resolved automatically by Claude Code when the plugin is installed, or set to the `--plugin-dir` path during development.\n\n## Workflow checklist\n\nCopy this and tick boxes as you progress:\n\n```\nTask Progress:\n- [ ] Step 0: Verify prerequisites — try `apify --version && apify info`; if unavailable, check for `call-actor` MCP tool; if neither, tell user to install apify CLI or Apify MCP connector. Also verify: `python3 -c \"from readability import Document; print('OK')\"` (install: `pip install readability-lxml lxml`)\n- [ ] Step 1: Build queries (look up company in data\u002Fcompanies.json or construct manually)\n- [ ] Step 2: Discovery — pick 8-12 sources by region, run 2-phase Google News\n- [ ] Step 3: Dedup + route (Tier 1 = whitelisted domain → verified extractor; Tier 2 = broad → rag-web-browser)\n- [ ] Step 4: Extract & clean (run extractor, then extract_and_clean.py)\n- [ ] Step 5: Output Tier 1 + Tier 2 tables to user\n```\n\n## Constraints\n\n### Allowed Apify Actors (exhaustive — do NOT use others)\n\n| Actor | Purpose |\n|-------|---------|\n| `data_xplorer\u002Fgoogle-news-scraper-fast` | Google News discovery |\n| `louvre\u002Frss-news-aggregator` | RSS discovery |\n| `rodrigo_pacelli\u002Fheadline-news-scraper` | Headline discovery |\n| `jamie_tran\u002Fbloomberg-article-scraper` | Bloomberg extraction |\n| `romy\u002Fbloomberg-news-scraper` | Bloomberg fallback |\n| `workhard3000\u002Fnews-intelligence-rag-extractor` | Paywall extraction |\n| `apify\u002Frag-web-browser` | Free\u002Fsoft-paywall + Tier 2 |\n| `stanvanrooy6\u002Funiversal-ai-web-scraper` | Hard paywall (Barron's, MarketWatch) — $0.25\u002Fpage |\n\nDo NOT use any other actor. Do NOT use WebSearch, WebFetch, or browser tools.\n\n### Extractor routing (mandatory — do NOT substitute)\n\n| Extractor | Domains |\n|-----------|---------|\n| `jamie_tran\u002Fbloomberg-article-scraper` | bloomberg.com |\n| `workhard3000\u002Fnews-intelligence-rag-extractor` | ft.com, wsj.com, economist.com, morningstar.com, asia.nikkei.com, caixinglobal.com, zawya.com, euobserver.com, reuters.com |\n| `apify\u002Frag-web-browser` | cnbc.com, forbes.com, investors.com, lesechos.fr, afr.com, scmp.com, euronews.com, intellinews.com, handelsblatt.com, politico.eu, eubusiness.com, eureporter.co, ecb.europa.eu, + all 7 CEE Local |\n| `stanvanrooy6\u002Funiversal-ai-web-scraper` | barrons.com, marketwatch.com |\n| REST API (presscorner) | ec.europa.eu |\n\nFull per-source config: [reference\u002FSOURCE_CONFIGS.md](reference\u002FSOURCE_CONFIGS.md). Machine-readable: [data\u002Fsources.json](data\u002Fsources.json).\n\n## Pipeline\n\n### Step 1: Build queries\n\nLook up company in `${CLAUDE_PLUGIN_ROOT}\u002Fdata\u002Fcompanies.json`. Key fields under `queries`: `gnews_en`, `gnews_cz`, `bloomberg`.\n\nFor non-portfolio companies, construct manually: quoted full legal name + ticker OR variant + geographic qualifier.\n\n**Query rules:**\n- Use `\"InPost SA\"` not `InPost` (quoted full names avoid false positives — see [reference\u002FEUROPEAN_COMPANIES_GUIDE.md](reference\u002FEUROPEAN_COMPANIES_GUIDE.md))\n- Per-source `site:` operator: `site:bloomberg.com \"InPost SA\" OR \"INPST\"`\n- FT tip: use `site:ft.com\u002Fcontent\u002F` (bare `ft.com` returns stock-data pages)\n- Valid timeframes: `\"1h\"`, `\"1d\"`, `\"7d\"`, `\"1y\"`, `\"all\"` (NOT `\"30d\"`)\n- Tickers \u003C 4 chars: always pair with full company name\n- ALWAYS set `decodeUrls: true` on Google News input\n\n### Step 2: Discovery\n\nDo NOT search all 33 sources. Pick 8–12 based on company region.\n\n#### Regional priorities\n\n| Region | Priority Sources |\n|--------|------------------|\n| **CZ** | ČTK, IntelliNews, Reuters, Bloomberg, POLITICO EU, FT, Handelsblatt |\n| **PL** | PAP, IntelliNews, Reuters, Bloomberg, POLITICO EU, FT |\n| **HU** | Telex.hu, HVG.hu, VG.hu, IntelliNews, Reuters, Bloomberg |\n| **BG** | BTA, IntelliNews, Reuters, Bloomberg, Euronews |\n| **SK** | TASR, IntelliNews, Reuters, Bloomberg, Handelsblatt |\n| **Western Europe** | Bloomberg, Reuters, FT, Handelsblatt, Les Echos, POLITICO EU |\n| **US \u002F Global** | Bloomberg, Reuters, WSJ, FT, CNBC, Forbes, Barron's |\n| **Asia \u002F MENA** | Bloomberg, Reuters, SCMP, Nikkei, Caixin, Zawya |\n| **EU Regulatory** | POLITICO EU, EUobserver, EUbusiness, EU Reporter, EC Press Corner, ECB |\n\n#### Two-phase Google News strategy\n\n**Phase 1 — Targeted** (per priority source, with `site:`):\n\n```bash\napify call data_xplorer\u002Fgoogle-news-scraper-fast \\\n  --input '{\"keywords\":[\"site:bloomberg.com \\\"InPost SA\\\" OR \\\"INPST\\\"\"],\"maxArticles\":10,\"timeframe\":\"7d\",\"region_language\":\"US:en\",\"decodeUrls\":true,\"proxyConfiguration\":{\"useApifyProxy\":true,\"apifyProxyGroups\":[\"RESIDENTIAL\"]}}' \\\n  --user-agent apify-awesome-skills\u002Fapify-financial-news \\\n  --output-dataset > discovery_bloomberg.json\n```\n\n**Phase 2 — Broad** (always run, no `site:` operator). Classify results by domain in Step 3 — whitelisted → Tier 1, others → Tier 2.\n\n**CEE local-language discovery**: For CEE companies, run additional queries with `region_language` set to `CZ:cs`, `PL:pl`, `HU:hu`, `BG:bg`, `SK:sk`. See `region_language` field per source in [data\u002Fsources.json](data\u002Fsources.json).\n\n#### EC Press Corner — direct REST API (no Actor)\n\n```bash\ncurl -s \"https:\u002F\u002Fec.europa.eu\u002Fcommission\u002Fpresscorner\u002Fapi\u002Fdocuments?reference=IP\u002F26\u002F614&language=en\"\n```\n\nParse `IP_XX_NNN` reference IDs from Google News titles to construct API calls.\n\n#### RSS \u002F Headline discovery (optional)\n\nFor sources with RSS, you can supplement GNews with `louvre\u002Frss-news-aggregator` (max 10 feeds per run; split into batches). For 6 sources, `rodrigo_pacelli\u002Fheadline-news-scraper` works (CNBC, SCMP, Nikkei, Caixin, Zawya tag-pages-only, Handelsblatt). RSS\u002Fheadline output is unfiltered — filter client-side by company name in title\u002Fdescription. Full feed list: [reference\u002FPIPELINE_DETAIL.md](reference\u002FPIPELINE_DETAIL.md).\n\n### Step 3: Dedup & route\n\n1. Collect URLs from all discovery runs.\n2. Classify by domain: whitelist (33 Tier 1 sources) → Tier 1; other → Tier 2.\n3. Filter non-article URLs: `\u002Fquote\u002F`, `\u002Fstock\u002F`, `\u002Fsitemap`, `\u002Fauthor\u002F`, `\u002Ftag\u002F`, `\u002Fkey-metrics\u002F`, `\u002Fnewsletters\u002F`, `\u002Ftopic\u002F`, `\u002Fprofile\u002F`, `redirectUrl=`.\n4. Filter by company name\u002Fticker in title.\n5. Deduplicate (URL normalize).\n6. Route Tier 1 URLs to verified extractor per routing table.\n7. Route Tier 2 URLs to `apify\u002Frag-web-browser`.\n\n**Low-coverage fallback** (\u003C 3 articles): broaden timeframe to `\"1y\"`, run Phase 2 if skipped, try local-language queries.\n\n### Step 4: Extract & clean\n\nRun the extractor per the routing table. For `rag-web-browser` calls, use `outputFormats: [\"html\"]`.\n\nAfter extraction, run `extract_and_clean.py` on the dataset to strip nav\u002Fmenus\u002Ffooters via readability-lxml. The script auto-detects format: HTML cleaned via readability-lxml, already-clean output (Bloomberg scraper, workhard3000) passes through.\n\n```bash\nDATASET_ID=$(apify call apify\u002Frag-web-browser \\\n  --input '{\"query\":\"\u003CARTICLE_URL>\",\"maxResults\":1,\"outputFormats\":[\"html\"],\"requestTimeoutSecs\":40,\"proxyConfiguration\":{\"useApifyProxy\":true,\"apifyProxyGroups\":[\"RESIDENTIAL\"]},\"removeCookieWarnings\":true}' \\\n  --user-agent apify-awesome-skills\u002Fapify-financial-news \\\n  --json | jq -r '.defaultDatasetId')\n\npython3 ${CLAUDE_PLUGIN_ROOT}\u002Fskills\u002Fapify-financial-news\u002Freference\u002Fscripts\u002Fextract_and_clean.py \"$DATASET_ID\"\n```\n\nThe `--json` flag returns run metadata including `defaultDatasetId`. Errors produce non-zero exit code so the pipeline fails fast.\n\n### Step 5: Output\n\nTwo tables to the user — **Tier 1 (verified)** and **Tier 2 (broad)**. Per article: source, title, author, date, char count, URL.\n\n```markdown\n## News Intelligence: InPost (INPST.AS) — Last 7 days\n\n### Tier 1 — Verified Sources (2)\n| Source | Title | Author | Date | Chars | URL |\n|--------|-------|--------|------|-------|-----|\n| bloomberg.com | InPost Readies AI Shopping Assistant | K. Krasuski | 2026-03-19 | 7,577 | … |\n\n### Tier 2 — Broad Discovery (5)\n| Source | Title | Date | Chars | URL |\n|--------|-------|------|-------|-----|\n| seekingalpha.com | InPost expands parcel locker network | 2026-03-18 | 1,200 | … |\n\n*Sources: 6 verified queried | 5 broad | Cost: $0.15*\n```\n\n## Macro context\n\nFor country-level economic context, use these alongside news scans:\n\n- **ING Think** (`think.ing.com`) — daily CEE FX\u002Frates via `apify\u002Frag-web-browser` (~11K chars). Best free open-access CEE macro source.\n- **IMF** (`imf.org`) — Article IV concluding statements via `apify\u002Frag-web-browser` (~22K chars).\n- **ECB** (`ecb.europa.eu`) — already in Tier 1.\n- Central banks (ČNB, NBP, MNB, BNB, NBS) — direct URL extraction; see [reference\u002FMACRO_SOURCES.md](reference\u002FMACRO_SOURCES.md).\n\n## Critical gotchas\n\n- **ALWAYS `decodeUrls: true`** in Google News (encoded redirects break ALL extractors).\n- **\"InPost\" is ambiguous** — matches \"post-Maduro\". Use `\"InPost SA\"` for precision.\n- **RSS max 10 feeds per run** — split into batches.\n- **Zawya headline-scraper returns tag pages, NOT articles** — exclude from headline runs.\n- **Reuters needs RESIDENTIAL proxy** — without it, returns 386 chars.\n- **Reuters: rag-web-browser returns 0 chars on ~60% of URLs** — use workhard3000 only.\n- **Morningstar `.co.uk` URLs fail** with workhard3000 — use `.com` URLs for extraction.\n- **WSJ livecoverage pages fail** — skip URLs matching `wsj.com\u002Flivecoverage\u002F`.\n- **FT: rag-web-browser returns 16 chars ('Client Challenge')** — use workhard3000.\n- **Forbes: workhard3000 returns 0 chars** — use rag-web-browser.\n- **Barron's \u002F MarketWatch cost $0.25\u002Fpage** — use selectively for high-value articles.\n- **Caixin URLs must be complete** — truncated URLs fail extraction.\n- **EC Press Corner is an Angular SPA** — `rag-web-browser` returns 0 chars. Use REST API.\n\nFull failure-mode catalog: [reference\u002FPIPELINE_DETAIL.md](reference\u002FPIPELINE_DETAIL.md), [reference\u002FSOURCE_CONFIGS.md](reference\u002FSOURCE_CONFIGS.md).\n\n## Reference\n\n- [data\u002Fsources.json](data\u002Fsources.json) — machine-readable: 33 sources × discovery × extractor × cost × gotchas\n- [reference\u002FSOURCE_CONFIGS.md](reference\u002FSOURCE_CONFIGS.md) — per-source curl examples, run IDs, output samples\n- [reference\u002FPIPELINE_DETAIL.md](reference\u002FPIPELINE_DETAIL.md) — RSS feeds, headline sources, warnings, failed paths, source quick-reference table\n- [reference\u002FMACRO_SOURCES.md](reference\u002FMACRO_SOURCES.md) — ING Think, IMF, central banks\n- [reference\u002FEUROPEAN_COMPANIES_GUIDE.md](reference\u002FEUROPEAN_COMPANIES_GUIDE.md) — European company handling tips\n- [reference\u002FMORNING_NOTE_DETAIL.md](reference\u002FMORNING_NOTE_DETAIL.md) — HTML output spec (archived; out of scope for this skill)\n- [reference\u002Fscripts\u002Fextract_and_clean.py](reference\u002Fscripts\u002Fextract_and_clean.py), [reference\u002Fscripts\u002Fclean_article.py](reference\u002Fscripts\u002Fclean_article.py) — readability-lxml post-processors\n",{"data":35,"body":38},{"name":4,"description":6,"author":36,"author_url":37},"chocholous","https:\u002F\u002Fgithub.com\u002Fchocholous",{"type":39,"children":40},"root",[41,50,56,82,87,97,104,168,195,201,206,218,224,231,395,400,406,505,525,531,537,579,584,592,729,735,740,747,913,919,936,1039,1056,1122,1128,1163,1176,1182,1207,1213,1328,1345,1351,1371,1383,1552,1573,1579,1598,1931,1937,1942,2022,2028,2203,2218,2224,2298],{"type":42,"tag":43,"props":44,"children":46},"element","h1",{"id":45},"financial-news-intelligence",[47],{"type":48,"value":49},"text","Financial News Intelligence",{"type":42,"tag":51,"props":52,"children":53},"p",{},[54],{"type":48,"value":55},"Discover and extract financial news for portfolio companies via Apify Actors. Two modes:",{"type":42,"tag":57,"props":58,"children":59},"ul",{},[60,72],{"type":42,"tag":61,"props":62,"children":63},"li",{},[64,70],{"type":42,"tag":65,"props":66,"children":67},"strong",{},[68],{"type":48,"value":69},"Single company",{"type":48,"value":71}," — news scan for one company.",{"type":42,"tag":61,"props":73,"children":74},{},[75,80],{"type":42,"tag":65,"props":76,"children":77},{},[78],{"type":48,"value":79},"Portfolio scan",{"type":48,"value":81}," — same pipeline run across multiple companies.",{"type":42,"tag":51,"props":83,"children":84},{},[85],{"type":48,"value":86},"33 Tier 1 sources organized in 4 categories (Global \u002F Pan-European \u002F Institutional \u002F CEE Local). Tier 2 = broad Google News fallback for unverified domains.",{"type":42,"tag":51,"props":88,"children":89},{},[90,95],{"type":42,"tag":65,"props":91,"children":92},{},[93],{"type":48,"value":94},"Estimated cost",{"type":48,"value":96},": $0.10–0.50 per single company, $1–5 per full portfolio scan.",{"type":42,"tag":98,"props":99,"children":101},"h2",{"id":100},"prerequisites",[102],{"type":48,"value":103},"Prerequisites",{"type":42,"tag":57,"props":105,"children":106},{},[107,136,157],{"type":42,"tag":61,"props":108,"children":109},{},[110,112,118,120,126,128,134],{"type":48,"value":111},"Apify access — preferred: ",{"type":42,"tag":113,"props":114,"children":116},"code",{"className":115},[],[117],{"type":48,"value":8},{"type":48,"value":119}," CLI (",{"type":42,"tag":113,"props":121,"children":123},{"className":122},[],[124],{"type":48,"value":125},"npm install -g apify-cli && apify login",{"type":48,"value":127},"); fallback: Apify MCP connector (",{"type":42,"tag":113,"props":129,"children":131},{"className":130},[],[132],{"type":48,"value":133},"call-actor",{"type":48,"value":135}," tool). 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Use when creating new Actors, modifying existing ones, or troubleshooting Actor code.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2312,2313,2316,2319],{"name":9,"slug":8,"type":15},{"name":2314,"slug":2315,"type":15},"Automation","automation",{"name":2317,"slug":2318,"type":15},"Serverless","serverless",{"name":21,"slug":22,"type":15},2231,"https:\u002F\u002Fgithub.com\u002Fapify\u002Fagent-skills","2026-04-06T18:00:48.720637",{"slug":2324,"name":2324,"fn":2325,"description":2326,"org":2327,"tags":2328,"stars":2320,"repoUrl":2321,"updatedAt":2336},"apify-actorization","convert projects into Apify Actors","Convert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript\u002FTypeScript (SDK with Actor.init\u002Fexit), Python (async context manager), or any language (CLI wrapper). Use when migrating code to Apify, wrapping CLI tools as Actors, or adding Actor SDK to existing projects.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2329,2330,2331,2334,2335],{"name":9,"slug":8,"type":15},{"name":2314,"slug":2315,"type":15},{"name":2332,"slug":2333,"type":15},"Migration","migration",{"name":2317,"slug":2318,"type":15},{"name":21,"slug":22,"type":15},"2026-04-06T18:00:46.151104",{"slug":2338,"name":2338,"fn":2339,"description":2340,"org":2341,"tags":2342,"stars":2320,"repoUrl":2321,"updatedAt":2351},"apify-generate-output-schema","generate Apify Actor output schemas","Generate output schemas (dataset_schema.json, output_schema.json, key_value_store_schema.json) for an Apify Actor by analyzing its source code. Use when creating or updating Actor output schemas.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2343,2346,2347,2350],{"name":2344,"slug":2345,"type":15},"API Development","api-development",{"name":9,"slug":8,"type":15},{"name":2348,"slug":2349,"type":15},"Data Modeling","data-modeling",{"name":21,"slug":22,"type":15},"2026-04-06T18:00:50.07596",{"slug":2353,"name":2353,"fn":2354,"description":2355,"org":2356,"tags":2357,"stars":2320,"repoUrl":2321,"updatedAt":2373},"apify-sdk-integration","integrate Apify SDK into applications","Integrate Apify into an existing JavaScript\u002FTypeScript or Python application using the apify-client package. Use when adding web scraping, automation, or data extraction capabilities to an existing app via the Apify API.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2358,2359,2360,2363,2366,2369,2372],{"name":9,"slug":8,"type":15},{"name":2314,"slug":2315,"type":15},{"name":2361,"slug":2362,"type":15},"JavaScript","javascript",{"name":2364,"slug":2365,"type":15},"Python","python",{"name":2367,"slug":2368,"type":15},"SDK","sdk",{"name":2370,"slug":2371,"type":15},"TypeScript","typescript",{"name":21,"slug":22,"type":15},"2026-05-16T05:56:15.416714",{"slug":2375,"name":2375,"fn":2376,"description":2377,"org":2378,"tags":2379,"stars":2320,"repoUrl":2321,"updatedAt":2383},"apify-ultimate-scraper","scrape data across web platforms","Universal AI-powered web scraper for any platform. Scrape data from Instagram, Facebook, TikTok, YouTube, LinkedIn, X\u002FTwitter, Google Maps, Google Search, Google Trends, Reddit, Airbnb, Yelp, and 15+ more platforms. Use for lead generation, brand monitoring, competitor analysis, influencer discovery, trend research, content analytics, audience analysis, review analysis, SEO intelligence, recruitment, or any data extraction task.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2380,2381,2382],{"name":9,"slug":8,"type":15},{"name":2314,"slug":2315,"type":15},{"name":21,"slug":22,"type":15},"2026-04-06T18:00:47.419432",{"slug":2385,"name":2385,"fn":2386,"description":2387,"org":2388,"tags":2389,"stars":2396,"repoUrl":2397,"updatedAt":2398},"apify-cli","run and manage Apify Actors via CLI","Patterns for invoking the Apify CLI (`apify`) from agents. Covers authentication, creating\u002Frunning\u002Fpushing Actors, calling Actors in the cloud, and reading results from datasets and key-value stores.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2390,2391,2392,2395],{"name":9,"slug":8,"type":15},{"name":2314,"slug":2315,"type":15},{"name":2393,"slug":2394,"type":15},"CLI","cli",{"name":21,"slug":22,"type":15},232,"https:\u002F\u002Fgithub.com\u002Fapify\u002Fapify-cli","2026-07-02T07:39:43.018333",{"slug":4,"name":4,"fn":5,"description":6,"org":2400,"tags":2401,"stars":23,"repoUrl":24,"updatedAt":25},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2402,2403,2404,2405],{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},{"name":13,"slug":14,"type":15},{"name":21,"slug":22,"type":15},{"slug":2407,"name":2407,"fn":2408,"description":2409,"org":2410,"tags":2411,"stars":23,"repoUrl":24,"updatedAt":2421},"apify-financial-osint","gather social listening signals for portfolio companies","Social-listening signals for tracked portfolio companies via Apify Actors — Reddit sentiment (fatihtahta), Twitter\u002FX real-time mentions (kaitoeasyapi pay-per-result), Trustpilot service quality (getwally.net). Use when the user asks for sentiment, social media mentions, customer reviews, brand perception, crisis signals, OSINT, social listening, \"what are people saying about X\". Reads tracked companies from data\u002Fcompanies.json. Do NOT use for news (use apify-financial-news) or registry lookups (use apify-public-registries).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2412,2413,2416,2417,2420],{"name":9,"slug":8,"type":15},{"name":2414,"slug":2415,"type":15},"Marketing","marketing",{"name":13,"slug":14,"type":15},{"name":2418,"slug":2419,"type":15},"Sales","sales",{"name":21,"slug":22,"type":15},"2026-05-23T06:06:04.102658",{"slug":2423,"name":2423,"fn":2424,"description":2425,"org":2426,"tags":2427,"stars":23,"repoUrl":24,"updatedAt":2434},"apify-public-registries","lookup company data from European public registries","Look up official company data from European public registries across 11 countries\u002Fregions (CZ, SK, PL, DE, UK, NL, RO, HR, SE + EU-level + ESG). Covers company registration, ownership, financial filings, VAT status, ESG data. Use when the user asks to \"look up a company\", \"check registry\", \"find company info\", \"look up IČO\u002FKRS\u002FLEI\u002FCRN\", \"company due diligence\", \"check VAT status\", \"find ownership structure\", or needs official data from European registries. Reads tracked companies from data\u002Fcompanies.json. Some lookups use Python scripts (stdlib), some fall back to Apify actors for scraping-based registries.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2428,2429,2432,2433],{"name":9,"slug":8,"type":15},{"name":2430,"slug":2431,"type":15},"Compliance","compliance",{"name":18,"slug":19,"type":15},{"name":13,"slug":14,"type":15},"2026-05-23T06:06:05.323553",{"slug":2436,"name":2436,"fn":2308,"description":2437,"org":2438,"tags":2439,"stars":2449,"repoUrl":2450,"updatedAt":2451},"apify-agent","Build, run, debug, and deploy Apify Actors. Use when the user wants to create an Actor, mentions apify create \u002F apify run \u002F apify push, or is debugging an Actor's input schema, storages, or deployment.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2440,2441,2442,2445,2448],{"name":9,"slug":8,"type":15},{"name":2314,"slug":2315,"type":15},{"name":2443,"slug":2444,"type":15},"Debugging","debugging",{"name":2446,"slug":2447,"type":15},"Deployment","deployment",{"name":21,"slug":22,"type":15},0,"https:\u002F\u002Fgithub.com\u002Fapify\u002Fapify-agent","2026-07-30T05:53:40.745073",{"items":2453,"total":1004},[2454,2461,2469],{"slug":4,"name":4,"fn":5,"description":6,"org":2455,"tags":2456,"stars":23,"repoUrl":24,"updatedAt":25},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2457,2458,2459,2460],{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},{"name":13,"slug":14,"type":15},{"name":21,"slug":22,"type":15},{"slug":2407,"name":2407,"fn":2408,"description":2409,"org":2462,"tags":2463,"stars":23,"repoUrl":24,"updatedAt":2421},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2464,2465,2466,2467,2468],{"name":9,"slug":8,"type":15},{"name":2414,"slug":2415,"type":15},{"name":13,"slug":14,"type":15},{"name":2418,"slug":2419,"type":15},{"name":21,"slug":22,"type":15},{"slug":2423,"name":2423,"fn":2424,"description":2425,"org":2470,"tags":2471,"stars":23,"repoUrl":24,"updatedAt":2434},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2472,2473,2474,2475],{"name":9,"slug":8,"type":15},{"name":2430,"slug":2431,"type":15},{"name":18,"slug":19,"type":15},{"name":13,"slug":14,"type":15}]