apify/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)

| 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