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monitoring-tech-acquisition-news-google — Claude Code skill: install

This skill searches Google for technology acquisition news and sorts results by deal status. Use it to review M&A activity in a sector or research a company.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add apidojo-io/apidojo-skills --skill monitoring-tech-acquisition-news-google -a claude-code
Open on GitHub

What monitoring-tech-acquisition-news-google does

The skill runs Apify’s Google Search Scraper with search terms, then filters and classifies the results. Its output can include deal announcements, the acquiring and target companies, signals about deal size, and strategic rationale. Use scripts/run_actor.js to save results as CSV or JSON.

Set APIFY_TOKEN in the environment or in a .env file before running it. Apify MCP is another option when that server is installed. The skill separates official announcements from press reports, speculation, and denials; early reports without an official release are marked unconfirmed. The actor will not run without an Apify token.

What it helps with

  • find recent technology company acquisitions
  • track M&A activity in a selected sector
  • collect reports naming buyers and acquired companies
  • sort confirmed deals from press reports and speculation

Example prompts for the agent

  • Find recent cybersecurity company acquisitions and separate official announcements from rumors.
  • Track buyers in the cloud services sector and save the results as CSV.
  • Search for technology merger news and highlight signals about deal size.

How to install monitoring-tech-acquisition-news-google

1Skills CLI (Vercel)

npx skills add apidojo-io/apidojo-skills --skill monitoring-tech-acquisition-news-google -a claude-code

2Manually: put the files in place

~/.claude/skills/monitoring-tech-acquisition-news-google/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/monitoring-tech-acquisition-news-google/

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

Questions about monitoring-tech-acquisition-news-google

How do I install monitoring-tech-acquisition-news-google in Claude Code?

Run npx skills add apidojo-io/apidojo-skills --skill monitoring-tech-acquisition-news-google -a claude-code. The skill file is placed at ~/.claude/skills/monitoring-tech-acquisition-news-google/SKILL.md.

What does monitoring-tech-acquisition-news-google do?

It searches Google for technology acquisition news through Apify’s Google Search Scraper, classifies results, and can save them as CSV or JSON.

What do I need to run the skill?

Set APIFY_TOKEN in the environment or a .env file. If Apify MCP is installed, the skill can use it to run the scraper.

Source text

SKILL.md · Apache-2.0
---
name: monitoring-tech-acquisition-news-google
description: >
  Monitors tech acquisition news and M&A activity using apidojo's Google Search scraper. Triggers when the user asks to: track tech acquisition news, monitor M&A activity in a sector on Google, find recent tech company acquisitions, track acquisition announcements in a technology category, monitor who is being acquired in a startup ecosystem, find companies that were recently acquired or merged, or research M&A trends in an industry.
  Returns acquisition announcements, acquirer and target company, deal size signals, and strategic rationale.
  Ideal for M&A analysts, startup founders, investors, and competitive intelligence teams.
license: Apache-2.0
metadata:
  author: apidojo
  version: "1.0"
  apify-actor: apidojo/google-search-scraper
---

# Monitoring Tech Acquisition News Google

Executes monitoring tech acquisition news google 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 |
|-----------|------|----------|---------|-------|
| `startUrls` | array | Optional | `[]` | Google search URLs |
| `searchTerms` | array | Optional | `[]` | Keywords to search on Google |
| `countryCode` | string | Optional | `US` | Country for Google search (e.g. `US`, `GB`, `TR`) |
| `languageCode` | string | Optional | — | Language for results (e.g. `en`) |
| `maxItems` | number | Optional | Unlimited | Maximum results to return across all queries |
| `maxPagesPerQuery` | integer | Optional | `1` | Maximum result pages per query |
| `mobileResults` | boolean | Optional | `false` | Fetch mobile SERP layout |
| `customMapFunction` | string | Optional | — | JavaScript function to transform each output object |

## Workflow

```
Progress:
- [ ] Step 1: Define parameters
- [ ] Step 2: Run google-search-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~google-search-scraper" \
  --input '{"param": "value"}'

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

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~google-search-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~google-search-scraper"
Input:
{
  "searchTerms": ["[SECTOR] acquisition 2026", "[SECTOR] acquired", "[COMPANY] acquires"],
  "maxItems": 100
}
```

**REST API fallback:**
```bash
curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~google-search-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms": ["[SECTOR] acquisition 2026", "[SECTOR] acquired", "[COMPANY] acquires"], "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: CONFIRMED (official announcement) | REPORTED (press rumor) | RUMORED (speculation) | DENIED
```

### Step 4: Score Each Result

```
score = deal_significance = (named_price ? deal_value/1000000 : 0.5) * 0.50 + (acquirer_is_public ? 1 : 0.5) * 0.30 + (coverage_from_tier1_pub ? 1 : 0.5) * 0.20
```

### Step 5: Edge Cases

- **M&A news often breaks before official press releases; use Google News search type to catch breaking reports, and flag STATUS = UNCONFIRMED until official press release found**

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 Tech Acquisition News Google
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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