apify-financial-osint

tarafından apify

Apify Aktörleri aracılığıyla takip edilen portföy şirketleri için sosyal dinleme sinyalleri — Reddit duyarlılığı (fatihtahta), Twitter/X gerçek zamanlı bahisleri (kaitoeasyapi…

npx skills add https://github.com/apify/awesome-skills --skill apify-financial-osint

Financial OSINT — Social Listening

Discover and quantify what the internet is saying about portfolio companies. Three verified Apify Actors only — Reddit (sentiment + threaded discussion), Twitter/X (real-time mentions, crisis monitoring), Trustpilot (customer satisfaction). All actors verified against real demo data with ≥98% success rate.

Prerequisites

  • 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.
  • Companies data at ${CLAUDE_PLUGIN_ROOT}/data/companies.json (read fields: queries.reddit, queries.twitter, trustpilot_urls, identifiers.ticker)
  • Per-company routing pre-computed at ${CLAUDE_PLUGIN_ROOT}/skills/apify-financial-osint/data/osint-targets.json

${CLAUDE_PLUGIN_ROOT} is the plugin's root directory (where .claude-plugin/ lives). It is resolved automatically by Claude Code when the plugin is installed, or set to the --plugin-dir path during development.

Workflow checklist

Copy this and tick boxes as you progress:

Task Progress:
- [ ] Step 0: Verify Apify access — 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
- [ ] Step 1: Pick actor(s) by signal type — see "Choose Actor by Signal" table
- [ ] Step 2: Build input — read data/osint-targets.json or construct from data/companies.json
- [ ] Step 3: Run actor via apify CLI
- [ ] Step 4: Output — present top results with sentiment + engagement signals

Constraints

Allowed Apify Actors (exhaustive — do NOT use others)

ActorPurposeCostSuccess rate
fatihtahta/reddit-scraper-search-fastReddit sentiment, acquisition reactions, brand perception$1.49 / 1k results98.4% (40,787 runs/30d)
kaitoeasyapi/twitter-x-data-tweet-scraper-pay-per-result-cheapestReal-time mentions, crisis monitoring, dealflow signals$0.25 / 1k tweets99.7% (4.3/5, 58 reviews)
getwally.net/trustpilot-reviews-scraperService quality, complaint patterns (telcos, e-commerce, banks)$3.00 / 1k resultsverified working

Do NOT use any other actor. Do NOT use WebSearch, WebFetch, or browser tools.

Choose Actor by Signal

If you needUse ActorWhen NOT to use
Sentiment / discussion threads / reactions to corporate eventsfatihtahta/reddit-scraper-search-fastIf company has no consumer base (B2B fintech, biotech) — expect <5 posts
Real-time mentions / crisis signals / dealflow chatterkaitoeasyapi/twitter-x-data-tweet-scraper-pay-per-result-cheapestIf you need >1 week historical depth — Twitter API limits
Customer satisfaction / service quality complaintsgetwally.net/trustpilot-reviews-scraperIf company has no Trustpilot page (B2B, holding companies) — see verified URL list in reference/osint-actor-schemas.md Section 3

Pipeline

Step 1: Pick actor(s)

For portfolio companies, look up the company in data/osint-targets.json — it pre-computes which actors to run with templated inputs. Routing rule (mirrors how the file was built):

  • queries.reddit non-empty → run Reddit actor
  • queries.twitter non-empty → run Twitter actor (always set for tracked companies)
  • trustpilot_urls non-empty → run Trustpilot actor

For ad-hoc / non-portfolio targets, construct input from scratch (see Step 2).

Step 2: Build input

Reddit input (key fields)

FieldTypeDefaultNotes
queriesarray of stringrequired (one of queries / urls / subredditName)Global Reddit-wide search terms.
maxPostsinteger50000 (!)ALWAYS set explicitly — typical 30-50 for scans, 100-200 for deep-dives.
scrapeCommentsbooleanfalseSet true to extract threaded discussion.
maxCommentsinteger50000 (!)Only used when scrapeComments: true. Typical 5–10.
sortenum"relevance"One of relevance, hot, top, new, comments. (NOT rising / best.)
timeframeenum"all"One of all, year, month, week, day, hour. Must be >= dateFrom–dateTo range.
dateFromstringYYYY-MM-DD. Post-fetch filter: keep posts from this date onward.
dateTostringYYYY-MM-DD. Post-fetch filter: keep posts up to this date.

Example:

apify call fatihtahta/reddit-scraper-search-fast \
  --input '{"queries":["InPost FedEx acquisition"],"maxPosts":50,"scrapeComments":true,"maxComments":10,"sort":"relevance","timeframe":"month"}' \
  --user-agent apify-awesome-skills/apify-financial-osint

Twitter/X input (key fields)

FieldTypeDefaultNotes
twitterContentstringOne of twitterContent / tweetIDs / searchTerms. Twitter advanced-search syntax (OR, -, from:, since:).
tweetIDsarray of stringPlural — not tweetId.
searchTermsarray of stringEach term gets maxItems results independently.
maxItemsinteger200REQUIRED — actor fails without it. Pay-per-result.
queryTypeenum"Latest"One of Latest, Top, Photos, Videos.
langstring"en"ISO 639-1. Set cs/pl/hu/bg/sk/tr for single-country B2C; omit for multilingual.
since / untilstringFormat: YYYY-MM-DD_HH:MM:SS_UTC (NOT ISO 8601).
filter:news / filter:media / min_faves / min_retweetsvariousEngagement / content filters.

Example:

apify call kaitoeasyapi/twitter-x-data-tweet-scraper-pay-per-result-cheapest \
  --input '{"twitterContent":"InPost FedEx acquisition OR INPST","maxItems":100,"queryType":"Latest","since":"2026-01-01_00:00:00_UTC","filter:news":true}' \
  --user-agent apify-awesome-skills/apify-financial-osint

Trustpilot input (only 2 fields exist!)

FieldTypeRequiredNotes
startUrlsarray of {"url": "..."} objectsYesNOT plain strings — array of objects.
limitintegerNo (default 1000)Set lower to control cost ($3/1k).

Example:

apify call getwally.net/trustpilot-reviews-scraper \
  --input '{"startUrls":[{"url":"https://www.trustpilot.com/review/inpost.pl"}],"limit":50}' \
  --user-agent apify-awesome-skills/apify-financial-osint

Older docs reference fields like maxItems, includeStatistics, includeCompanyDetails, onlyNewerThan — these do NOT exist on this actor.

Step 3: Cost-bound the run

Always cap output before running. Defaults are dangerously high.

ActorCap fieldPortfolio scanDeep-dive
RedditmaxPosts30–50100–200
Reddit commentsmaxComments5–10 (only if scrapeComments: true)20–50
Twitter/XmaxItems50–100200–500
Trustpilotlimit30–50100–200

Twitter and Trustpilot are pay-per-result — every returned item is billed.

Step 4: Run

Single example pulling Reddit threads + Twitter mentions for InPost (driven by data/osint-targets.json):

apify call fatihtahta/reddit-scraper-search-fast \
  --input "$(jq -c '.targets[] | select(.company_id=="inpost") | .inputs.reddit' \
    ${CLAUDE_PLUGIN_ROOT}/skills/apify-financial-osint/data/osint-targets.json)" \
  --user-agent apify-awesome-skills/apify-financial-osint \
  --output-dataset > reddit_inpost.json

Full per-actor input schema (all 51 Twitter properties, every Reddit enum, every Trustpilot edge case) plus 30+ example invocations: reference/osint-actor-schemas.md.

Step 4b: Post-filter Reddit results

Reddit search ignores quotes and matches partial words ("InPost" matches "in post game thread"). After fetching, filter results client-side: keep only posts where any of the company's search queries appears as a whole word (case-insensitive) in title or body. Use the queries array from data/osint-targets.json for matching (these are the terms the company is actually known by). Normalise diacritics before comparing (Š↔S, ö↔o, etc.).

Expect 90–95% of raw Reddit results to be false positives. This is normal — maxPosts is set to 200 to compensate.

Step 5: Output

Key output fields per actor:

ActorDate fieldDate formatURL fieldEngagement fields
Redditcreated_utcISO 8601 (2026-05-01T17:26:41.000Z)canonical_urlscore, num_comments
TwittercreatedAtNon-standard (Fri May 01 17:35:21 +0000 2026)urllikeCount, retweetCount, replyCount
TrustpilotdateISO 8601 (2026-01-27T21:53:45.000Z)url (review ID, not company page)ratingValue (string "1"–"5")

Present top results with:

  • Sentiment hint (positive / negative / neutral) where derivable from text
  • Engagement — see table above
  • Author / handle
  • Date — normalise to YYYY-MM-DD for display
  • Permalink

Example output for a sentiment scan:

## OSINT Scan: InPost — Last 30 days

### Reddit (3 posts, 47 comments analyzed)
| Title | Subreddit | Score | Sentiment | Date | URL |
|---|---|---|---|---|---|
| InPost lockers in UK getting better? | r/unitedkingdom | 124 | positive | 2026-04-12 | … |
| Anyone else missing parcels? | r/poland | 38 | negative | 2026-04-09 | … |

### Twitter/X (87 tweets)
| Tweet (truncated) | Author | Likes | Replies | Date | URL |
|---|---|---|---|---|---|
| FedEx-InPost rollout looks promising… | @logistics_eu | 412 | 27 | 2026-04-22 | … |

### Trustpilot (50 reviews — avg 3.2 / 5)
| Rating | Title | Author | Date | URL |
|---|---|---|---|---|
| 5 | Good system, very efficient | Yeison S. | 2026-03-10 | … |
| 1 | Parcel never delivered | Anna K. | 2026-04-18 | … |

Per-company routing

data/osint-targets.json maps each portfolio company → which OSINT actors to run, with pre-built input templates derived from data/companies.json. Coverage as of v1.0: 31 entries (30 portfolio + group), Reddit 27, Twitter 31, Trustpilot 5, all-three 5, Twitter-only 4. Empty-actor entries reflect verified absence (e.g., MONETA / CETIN / SOTIO have no Trustpilot page).

Critical gotchas (high-frequency mistakes)

  • Reddit maxPosts default is 50000 — ALWAYS set explicitly (typical: 30–50 for scans).
  • Reddit maxComments default is 50000 — set low whenever scrapeComments: true.
  • Reddit subredditKeywords is an array, not a string.
  • Reddit sort enum has no "rising" / "best" — only relevance, hot, top, new, comments.
  • Reddit includeNsfw — lowercase "sfw" (not includeNSFW).
  • Twitter maxItems is REQUIRED — actor fails without it. Pay-per-result.
  • Twitter since / until format is YYYY-MM-DD_HH:MM:SS_UTC (NOT ISO 8601).
  • Twitter tweetIDs is plural array — not tweetId.
  • Twitter lang default is "en" — set explicitly or omit for all languages.
  • Trustpilot startUrls must be array of objects with url key — NOT plain strings.
  • Trustpilot has ONLY 2 input fields (startUrls, limit) — older docs reference maxItems, includeStatistics, includeCompanyDetails, onlyNewerThan that DO NOT EXIST.
  • Trustpilot ratingValue is a STRING ("1"–"5"), not integer — parse before aggregating.
  • Trustpilot has no date filter — actor returns most recent first up to limit; post-filter by date field.
  • Trustpilot URLs verified per company — see "Known Trustpilot URLs" table in reference/osint-actor-schemas.md Section 3. Some companies have NO Trustpilot page (B2B holdings, biotech) — running the actor returns 0 reviews.

Full per-actor schemas + 30+ example invocations: reference/osint-actor-schemas.md.

Reference

apify tarafından daha fazla skill

bug-triage
apify
Apify/apify-mcp-server üzerindeki açık hata sorunlarını triyajla. Analiz et, yanıt taslağı hazırla, onay al ve yayınla.
official
apify-influencer-brand-collabs
apify
Apify Aktörlerini zincirleyerek Instagram marka–içerik üreticisi ortaklıklarını keşfedin. Kullanıcı bir markayla kimlerin iş birliği yaptığını, bir içerik üreticisinin hangi markalarla ücretli…
official
dig
apify
Apify MCP sunucusunda iş keşfetme, planlama ve özellik belirleme için esnek bir beceri. Kaynak dosyaları DÜZENLEMEYİN — bu beceri yalnızca anlama ve planlama içindir.
official
apify-financial-news
apify
33 doğrulanmış Tier 1 kaynaktan (Bloomberg, Reuters, FT, WSJ, IntelliNews, ČTK, PAP, BTA,…) takip edilen portföy şirketleri için finansal haberleri keşfedin ve çıkarın.
official
apify-actor-development
apify
Web kazıma, otomasyon ve veri işleme için sunucusuz bulut programları oluşturun, hata ayıklayın ve dağıtın. HTTP ve tarayıcı tabanlı tarama için entegre Crawlee, Playwright ve Cheerio kütüphaneleriyle JavaScript, TypeScript ve Python şablonlarını destekler. İzole depolama ile apify run aracılığıyla yerel test, girdi/çıktılar için şema doğrulama ve apify push ile Apify platformuna dağıtım içerir. Apify CLI kimlik doğrulaması ve .actor/actor.json dosyasında AI için zorunlu generatedBy meta verisi gerektirir...
official
apify-actorization
apify
Mevcut projeleri, dile özgü SDK entegrasyonu ile sunucusuz Apify Actor'lere dönüştürür. JavaScript/TypeScript (Actor.init() / Actor.exit() ile), Python (async context manager) ve CLI sarmalayıcı aracılığıyla herhangi bir dili destekler. Yapılandırılmış iş akışı sağlar: apify init ile iskelet oluşturma, SDK sarmalama uygulama, giriş/çıkış şemalarını yapılandırma, apify run ile yerel test etme ve apify push ile dağıtma. Giriş ve çıkış şeması doğrulaması, Docker konteynerleştirmesi ve isteğe bağlı olay başına ödeme içerir...
official
apify-generate-output-schema
apify
Bir Apify Actor için çıktı şemalarını (dataset_schema.json, output_schema.json, key_value_store_schema.json) kaynak kodunu analiz ederek oluşturur. Şu durumlarda kullanılır…
official
apify-ultimate-scraper
apify
55'ten fazla platform (Instagram, TikTok, YouTube, Facebook, Google Maps ve daha fazlası dahil) için en uygun Actor'ları seçen otomatik web kazıyıcı. 8 büyük platformda 55'ten fazla ön yapılandırılmış Actor'ı kapsar ve kullanım senaryosuna özel seçim rehberliği (potansiyel müşteri bulma, fenomen keşfi, marka izleme, rakip analizi, trend araştırması) sunar. Üç çıktı formatını destekler: hızlı sohbet görüntüleme, CSV dışa aktarma veya özelleştirilebilir sonuç limitleriyle JSON dışa aktarma. Karmaşık iş akışları için çoklu Actor desenlerini içerir...
official