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monitoring-vc-investor-activity-on-twitter — Claude Code skill: VC

This skill pulls investor tweets through apidojo's scraper, classifies the accounts and scores deal signals. Useful when you are raising.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add apidojo-io/apidojo-skills --skill monitoring-vc-investor-activity-on-twitter -a claude-code
Open on GitHub

What monitoring-vc-investor-activity-on-twitter does

The skill runs the apidojo/tweet-scraper and apidojo/twitter-user-scraper actors on Apify and turns the output into a table: investor handle, firm, investment thesis signals, recent activity, deal flow indicators. You drive it with a searchTerms array of Twitter advanced search queries, for example ["#AI lang:en", "from:NASA"]. Filters cover language, date range, minimum retweets and likes, and verified accounts only.

Five steps run in order: define parameters, run the scraper, classify results, score them, deliver output. Classification sorts people into ACTIVE_INVESTOR, PASSIVE_FOLLOWER, ANGEL and FIRM_PARTNER. The score adds four weighted parts: thesis tweet, portfolio mention, VC firm in bio, follower count. You can launch it with scripts/run_actor.js, through the Apify MCP server, or with a plain curl call to the REST API.

Set APIFY_TOKEN in your environment or a .env file before the first run. Without it neither the script nor the REST call goes through. One thing to watch: partners make investment decisions, associates and VPs do not, so the skill tells you to take the title from the bio. Under 20 results, it suggests broadening the queries and dropping secondary filters.

What it helps with

  • find investors tweeting about your sector right now
  • track funding announcements and deal signals on X
  • separate firm partners from associates and VPs
  • build a list of active investors in one vertical
  • cut noise with minimum likes and retweets

Example prompts for the agent

  • find investors actively posting about AI startups on X over the last month
  • run tweet-scraper on fintech queries and save the results as CSV
  • which firm partners mention portfolio companies most in this vertical

How to install monitoring-vc-investor-activity-on-twitter

1Skills CLI (Vercel)

npx skills add apidojo-io/apidojo-skills --skill monitoring-vc-investor-activity-on-twitter -a claude-code

2Manually: put the files in place

~/.claude/skills/monitoring-vc-investor-activity-on-twitter/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/monitoring-vc-investor-activity-on-twitter/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about monitoring-vc-investor-activity-on-twitter

How do I install monitoring-vc-investor-activity-on-twitter in Claude?

Run npx skills add apidojo-io/apidojo-skills --skill monitoring-vc-investor-activity-on-twitter -a claude-code. The skill file lands at ~/.claude/skills/monitoring-vc-investor-activity-on-twitter/SKILL.md.

What does this skill do?

It runs apidojo's tweet scraper on your search queries, classifies the accounts it finds as active investors, angels or firm partners, and scores them by deal signals.

What do I need before running it?

An APIFY_TOKEN in your environment or a .env file. Optionally install the Apify MCP server and run it through the apify:run-actor tool instead.

Source text

SKILL.md · Apache-2.0
---
name: monitoring-vc-investor-activity-on-twitter
description: >
  Monitors VC investor activity and deal signals on Twitter using apidojo's Tweet scraper. Triggers when the user asks to: monitor VC activity on Twitter, track what investors are tweeting about, find VCs who are actively investing in a sector on X, monitor deal flow signals from investor tweets, find investors who are looking for deals in a space, track funding announcements from VC firms on Twitter, or discover which investors are most active in a specific vertical.
  Returns investor handle, firm, investment thesis signals, recent activity, deal flow indicators.
  Ideal for startup founders fundraising, co-investors, and startup ecosystem analysts.
license: Apache-2.0
metadata:
  author: apidojo
  version: "1.0"
  apify-actors: apidojo/tweet-scraper, apidojo/twitter-user-scraper
---

# Monitoring Vc Investor Activity On Twitter

Executes monitoring vc investor activity on twitter using apidojo scrapers. Part of the apidojo intelligence skills library.

## Prerequisites

- `APIFY_TOKEN` environment variable set
- Optional: Apify MCP server installed

## Inputs

| Parameter | Type | Required | Default | Notes |
|-----------|------|----------|---------|-------|
| `searchTerms` | array | ✅ | `[]` | Twitter advanced search queries (e.g. `["#AI lang:en", "from:NASA"]`) |
| `sort` | string | Optional | `Top` | Sort order: `Latest`, `Top`, or `Latest+Top` |
| `tweetLanguage` | string | Optional | — | ISO 639-1 language code (e.g. `en`) |
| `maxItems` | number | Optional | Unlimited | Maximum tweets to return |
| `onlyVerifiedUsers` | boolean | Optional | `false` | Only tweets from verified users |
| `onlyTwitterBlue` | boolean | Optional | `false` | Only Twitter Blue subscribers |
| `onlyImage` | boolean | Optional | `false` | Only tweets with images |
| `onlyVideo` | boolean | Optional | `false` | Only tweets with videos |
| `onlyQuote` | boolean | Optional | `false` | Only quote tweets |
| `author` | string | Optional | — | Filter to a specific author handle |
| `inReplyTo` | string | Optional | — | Tweets replying to a specific handle |
| `mentioning` | string | Optional | — | Tweets mentioning a specific handle |
| `geotaggedNear` | string | Optional | — | Tweets near a location |
| `withinRadius` | string | Optional | — | Radius around geotaggedNear |
| `geocode` | string | Optional | — | Lat/lng + radius string |
| `placeObjectId` | string | Optional | — | Tweets tagged with a place |
| `minimumRetweets` | number | Optional | — | Minimum retweet count |
| `minimumFavorites` | number | Optional | — | Minimum like count |
| `minimumReplies` | number | Optional | — | Minimum reply count |
| `start` | string | Optional | — | Tweets after this date (YYYY-MM-DD) |
| `end` | string | Optional | — | Tweets before this date (YYYY-MM-DD) |
| `includeSearchTerms` | boolean | Optional | `false` | Add the matched search term to each tweet |
| `customMapFunction` | string | Optional | — | JavaScript function to transform each output object |

## Workflow

```
Progress:
- [ ] Step 1: Define parameters
- [ ] Step 2: Run tweet-scraper
- [ ] Step 3: Filter and classify results
- [ ] Step 4: Score by quality and relevance
- [ ] Step 5: Deliver output
```

### Step 2: Run the Actor


**Recommended — run_actor.js (handles waiting, output, and file saving automatically):**
```bash
# Quick answer (prints table to chat)
node scripts/run_actor.js \
  --actor "apidojo~tweet-scraper" \
  --input '{"param": "value"}'

# Save as CSV
node scripts/run_actor.js \
  --actor "apidojo~tweet-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.csv --format csv

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~tweet-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.json --format json
```
> `APIFY_TOKEN` must be set in environment or `.env` file.

**If Apify MCP is available:**
```
Tool: apify:run-actor
Actor: "apidojo~tweet-scraper"
Input:
{
  "searchTerms": ["investing in [SECTOR]", "excited about [SECTOR]", "looking for [SECTOR] startups", "portfolio company [SECTOR]"],
  "maxItems": 100
}
```

**REST API fallback:**
```bash
curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms": ["investing in [SECTOR]", "excited about [SECTOR]", "looking for [SECTOR] startups", "portfolio company [SECTOR]"], "maxItems": 100}'
```

Wait for `SUCCEEDED`. Fetch dataset:
```bash
curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"
```

### Step 3: Classify Results

```
classification: ACTIVE_INVESTOR (recent deal activity, thesis tweets) | PASSIVE_FOLLOWER (investor title but no deal signals) | ANGEL (individual, smaller checks) | FIRM_PARTNER (major VC firm affiliation)
```

### Step 4: Score Each Result

```
score = deal_signal_score = (tweeted_investment_thesis ? 1 : 0) * 0.35 + (tweeted_about_portfolio ? 1 : 0) * 0.25 + (bio_contains_VC_firm ? 1 : 0) * 0.25 + (followerCount > 5000 ? 1 : 0.5) * 0.15
```

### Step 5: Edge Cases

- **Distinguish actual investment partners from associates and VPs — partners make investment decisions; use title from bio for classification**

Additional fallbacks:
- **< 20 results**: Broaden search terms; remove secondary filters
- **No results**: Verify the search terms are correct; try alternate phrasings
- **Data quality issues**: Remove entries with missing key fields; note count in output

## Output Format

```
# Monitoring Vc Investor Activity On Twitter
Results: [N] | Date: [DATE]

| # | [Key Field] | [Metric 1] | [Metric 2] | [Classification] | [Score] |
|---|------------|-----------|-----------|-----------------|---------|
| 1 | [value] | [value] | [value] | [type] | [0.XX] |

## Summary
Top result: [description]
Key finding: [insight]
```

## Troubleshooting

**Too few results:** Broaden the primary search term; remove restrictive filters.
**Low quality results:** Apply minimum score threshold (≥ 0.50) to filter noise.
**Actor fails to run:** Verify API key; check actor status at apify.com/apidojo.

© apidojo · Apache-2.0 · apidojo-io/apidojo-skills

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