apify-financial-osint

name	apify-financial-osint
description	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).
author	chocholous
author_url	https://github.com/chocholous

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)

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.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)

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
Reddit	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
Reddit	created_utc	ISO 8601 (2026-05-01T17:26:41.000Z)	canonical_url	score, num_comments
Twitter	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 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

• 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