
apify-financial-osint
Social-listening signals for tracked portfolio companies via Apify Actors — Reddit sentiment (fatihtahta), Twitter/X 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/companies.json. Do NOT use for news (use apify-financial-news) or registry lookups (use apify-public-registries).
- Installs
- 123
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/apify/awesome-skills --skill apify-financial-osint- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads apify-financial-osint automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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:
apifyCLI (npm install -g apify-cli && apify login); fallback: Apify MCP connector (call-actortool). 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)
| Actor | Purpose | Cost | Success rate |
|---|---|---|---|
fatihtahta/reddit-scraper-search-fast | Reddit sentiment, acquisition reactions, brand perception | $1.49 / 1k results | 98.4% (40,787 runs/30d) |
kaitoeasyapi/twitter-x-data-tweet-scraper-pay-per-result-cheapest | Real-time mentions, crisis monitoring, dealflow signals | $0.25 / 1k tweets | 99.7% (4.3/5, 58 reviews) |
getwally.net/trustpilot-reviews-scraper | Service quality, complaint patterns (telcos, e-commerce, banks) | $3.00 / 1k results | verified working |
Do NOT use any other actor. Do NOT use WebSearch, WebFetch, or browser tools.
Choose Actor by Signal
| If you need | Use Actor | When NOT to use |
|---|---|---|
| Sentiment / discussion threads / reactions to corporate events | fatihtahta/reddit-scraper-search-fast | If company has no consumer base (B2B fintech, biotech) — expect <5 posts |
| Real-time mentions / crisis signals / dealflow chatter | kaitoeasyapi/twitter-x-data-tweet-scraper-pay-per-result-cheapest | If you need >1 week historical depth — Twitter API limits |
| Customer satisfaction / service quality complaints | getwally.net/trustpilot-reviews-scraper | If 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.redditnon-empty → run Reddit actorqueries.twitternon-empty → run Twitter actor (always set for tracked companies)trustpilot_urlsnon-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)
| Field | Type | Default | Notes |
|---|---|---|---|
queries | array of string | required (one of queries / urls / subredditName) | Global Reddit-wide search terms. |
maxPosts | integer | 50000 (!) | ALWAYS set explicitly — typical 30-50 for scans, 100-200 for deep-dives. |
scrapeComments | boolean | false | Set true to extract threaded discussion. |
maxComments | integer | 50000 (!) | Only used when scrapeComments: true. Typical 5–10. |
sort | enum | "relevance" | One of relevance, hot, top, new, comments. (NOT rising / best.) |
timeframe | enum | "all" | One of all, year, month, week, day, hour. Must be >= dateFrom–dateTo range. |
dateFrom | string | — | YYYY-MM-DD. Post-fetch filter: keep posts from this date onward. |
dateTo | string | — | YYYY-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)
| Field | Type | Default | Notes |
|---|---|---|---|
twitterContent | string | — | One of twitterContent / tweetIDs / searchTerms. Twitter advanced-search syntax (OR, -, from:, since:). |
tweetIDs | array of string | — | Plural — not tweetId. |
searchTerms | array of string | — | Each term gets maxItems results independently. |
maxItems | integer | 200 | REQUIRED — actor fails without it. Pay-per-result. |
queryType | enum | "Latest" | One of Latest, Top, Photos, Videos. |
lang | string | "en" | ISO 639-1. Set cs/pl/hu/bg/sk/tr for single-country B2C; omit for multilingual. |
since / until | string | — | Format: YYYY-MM-DD_HH:MM:SS_UTC (NOT ISO 8601). |
filter:news / filter:media / min_faves / min_retweets | various | — | Engagement / 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!)
| Field | Type | Required | Notes |
|---|---|---|---|
startUrls | array of {"url": "..."} objects | Yes | NOT plain strings — array of objects. |
limit | integer | No (default 1000) | Set lower to control cost ($3/1k). |
Example:
apify call getwally.net/trustpilot-reviews-scraper \
--input '{"startUrls":[{"url":"https://www.trustpilot.com/review/inpost.pl"}],"limit":50}' \
--user-agent apify-awesome-skills/apify-financial-osint
Older docs reference fields like maxItems, includeStatistics, includeCompanyDetails, onlyNewerThan — these do NOT exist on this actor.
Step 3: Cost-bound the run
Always cap output before running. Defaults are dangerously high.
| Actor | Cap field | Portfolio scan | Deep-dive |
|---|---|---|---|
maxPosts | 30–50 | 100–200 | |
| Reddit comments | maxComments | 5–10 (only if scrapeComments: true) | 20–50 |
| Twitter/X | maxItems | 50–100 | 200–500 |
| Trustpilot | limit | 30–50 | 100–200 |
Twitter and Trustpilot are pay-per-result — every returned item is billed.
Step 4: Run
Single example pulling Reddit threads + Twitter mentions for InPost (driven by data/osint-targets.json):
apify call fatihtahta/reddit-scraper-search-fast \
--input "$(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:
| Actor | Date field | Date format | URL field | Engagement fields |
|---|---|---|---|---|
created_utc | ISO 8601 (2026-05-01T17:26:41.000Z) | canonical_url | score, num_comments | |
createdAt | Non-standard (Fri May 01 17:35:21 +0000 2026) | url | likeCount, retweetCount, replyCount | |
| Trustpilot | date | ISO 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
maxPostsdefault is 50000 — ALWAYS set explicitly (typical: 30–50 for scans). - Reddit
maxCommentsdefault is 50000 — set low wheneverscrapeComments: true. - Reddit
subredditKeywordsis an array, not a string. - Reddit
sortenum has no"rising"/"best"— only relevance, hot, top, new, comments. - Reddit
includeNsfw— lowercase "sfw" (notincludeNSFW). - Twitter
maxItemsis REQUIRED — actor fails without it. Pay-per-result. - Twitter
since/untilformat isYYYY-MM-DD_HH:MM:SS_UTC(NOT ISO 8601). - Twitter
tweetIDsis plural array — nottweetId. - Twitter
langdefault is"en"— set explicitly or omit for all languages. - Trustpilot
startUrlsmust be array of objects withurlkey — NOT plain strings. - Trustpilot has ONLY 2 input fields (
startUrls,limit) — older docs referencemaxItems,includeStatistics,includeCompanyDetails,onlyNewerThanthat DO NOT EXIST. - Trustpilot
ratingValueis a STRING ("1"–"5"), not integer — parse before aggregating. - Trustpilot has no date filter — actor returns most recent first up to
limit; post-filter bydatefield. - Trustpilot URLs verified per company — see "Known Trustpilot URLs" table in
reference/osint-actor-schemas.mdSection 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
- data/osint-targets.json — per-company routing + pre-built actor inputs (31 entries)
- reference/osint-actor-schemas.md — verbatim source: all 4 actor schemas with portfolio examples (Section 4 Economic Calendar archived; out of scope for this skill — see PLAN.md)
- Shared portfolio data:
${CLAUDE_PLUGIN_ROOT}/data/companies.json
FAQ
What does the apify-financial-osint skill do?
Social-listening signals for tracked portfolio companies via Apify Actors — Reddit sentiment (fatihtahta), Twitter/X 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/companies.json. Do NOT use for news (use apify-financial-news) or registry lookups (use apify-public-registries).
How do I install apify-financial-osint?
Run npx skills add https://github.com/apify/awesome-skills --skill apify-financial-osint in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/apify-financial-osint/ (personal) or .claude/skills/apify-financial-osint/ (project).
Which AI agents can use apify-financial-osint?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is apify-financial-osint safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains apify-financial-osint?
It is published by apify in apify/awesome-skills, and it is an official skill from the maker of the technology it covers. It has 123 recorded installs.
More from apify/awesome-skills
apify-ecommerce
apify/awesome-skills
Scrape e-commerce data for pricing, reviews, bestsellers, and seller discovery across 30+ platforms including Amazon, Walmart, eBay, Shopify, WooCommerce, and more. Use when user asks about product prices, competitor analysis, store scraping, tech stack detection, food delivery, real estate, or marketplace intelligence.
apify-easy-competitive-intelligence
apify/awesome-skills
Open the skill to read its SKILL.md instructions.
apify-verified-email-finder
apify/awesome-skills
Open the skill to read its SKILL.md instructions.
apify-ads-intelligence
apify/awesome-skills
Research, spy on, and analyze ads across Meta (Facebook & Instagram), Google (Ads Transparency Center + paid search results), TikTok (Ads Library + Creative Center), LinkedIn Ad Library, and X (Twitter — promoted tweets, best-effort) using Apify Actors. Use when user asks about competitor ads, ad library research, winning creatives, ad copy analysis, landing page audits from ads, cross-platform ad audits, brand transparency checks, or any task involving paid ad creatives, advertiser data, or ad targeting from public ad libraries.
apify-link-prospecting-outreach
apify/awesome-skills
Open the skill to read its SKILL.md instructions.
apify-ai-search-visibility-tracker
apify/awesome-skills
Open the skill to read its SKILL.md instructions.
Popular business & finance skills
sales-enablement
coreyhaines31/marketingskills
When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific ROI analysis,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' 'buyer persona card,' 'battle card,' 'battlecard,' 'competitive one-pager,' 'win-loss analysis,' 'why are we losing deals,' 'loss reasons,' 'how do I respond to this objection,' 'prospect just said,' 'help my sales team,' 'sales materials,' or 'what should I give my sales reps,' 'cold call script,' or 'voicemail script.' Use this for any document or asset that helps a sales team close deals. For public competitor comparison pages, see competitors. For running buyer interviews or churn research, see customer-research. For marketing website copy, see copywriting. For cold outreach emails, see cold-email. For the offer being sold (bonuses, guarantees, pricing structure),
revops
coreyhaines31/marketingskills
When the user wants help with revenue operations, lead lifecycle management, or marketing-to-sales handoff processes. Also use when the user mentions 'RevOps,' 'revenue operations,' 'lead scoring,' 'outbound pipeline stages,' 'lead routing,' 'MQL,' 'SQL,' 'pipeline stages,' 'deal desk,' 'CRM automation,' 'marketing-to-sales handoff,' 'data hygiene,' 'leads aren't getting to sales,' 'pipeline management,' 'lead qualification,' or 'when should marketing hand off to sales.' Use this for anything involving the systems and processes that connect marketing to revenue. For cold outreach emails, see cold-email. For email drip campaigns, see emails. For pricing decisions, see pricing.
sales-funnel-blueprint
autonnel/autonnel-skills
Turn an offer into a concrete multi-step sales funnel spec - page-by-page structure, price ladder, copy outline and the metrics each step must hit. Use when asked to build a sales funnel, marketing funnel, landing page flow, lead magnet funnel, webinar funnel, tripwire or VSL funnel, when planning a product launch page flow, or when someone asks "what pages do I need" for selling something online.
pricing
coreyhaines31/marketingskills
When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' 'should I offer a free plan,' 'pricing page teardown,' 'pricing page audit,' 'is my pricing page AI-readable,' or 'can AI read my pricing.' Use this whenever someone is figuring out what to charge, how to structure their plans, or wants to audit a pricing page (for humans and for the AI agents that shortlist tools). For in-app upgrade screens, see paywalls. For offer construction (bonuses, guarantees, value framing, naming) on services/courses/coaching/high-ticket B2B, see offers.
cross-border-ecommerce
nexscope-ai/ecommerce-skills
Cross-border e-commerce expansion advisor. Scores target markets on 8 weighted dimensions (market size, ecommerce penetration, competition, regulatory complexity, logistics infrastructure, payment ecosystem, cultural distance, IP protection), compares 5 fulfillment models with cost and transit data, provides country-by-country tax/duty compliance guides (EU VAT/IOSS, UK VAT, US sales tax, CA GST, AU GST, JP consumption tax), maps local payment preferences by market, and builds a phased expansion roadmap. No API key required.
pricing-strategy
coreyhaines31/marketingskills
When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' or 'should I offer a free plan.' Use this whenever someone is figuring out what to charge or how to structure their plans. For in-app upgrade screens, see paywall-upgrade-cro.