merge: incorporate Apify community PR #4770

# Conflicts:
#	tools/src/aden_tools/credentials/__init__.py
#	tools/src/aden_tools/credentials/apify.py
#	tools/src/aden_tools/tools/__init__.py
#	tools/src/aden_tools/tools/apify_tool/__init__.py
#	tools/src/aden_tools/tools/apify_tool/apify_tool.py
#	tools/tests/tools/test_apify_tool.py

commit_message.txt

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+perf: reduce subprocess spawning in quickstart scripts (#4427)
+
+## Problem
+Windows process creation (CreateProcess) is 10-100x slower than Linux fork/exec.
+The quickstart scripts were spawning 4+ separate `uv run python -c "import X"` 
+processes to verify imports, adding ~600ms overhead on Windows.
+
+## Solution
+Consolidated all import checks into a single batch script that checks multiple 
+modules in one subprocess call, reducing spawn overhead by ~75%.
+
+## Changes
+- **New**: `scripts/check_requirements.py` - Batched import checker
+- **New**: `scripts/test_check_requirements.py` - Test suite  
+- **New**: `scripts/benchmark_quickstart.ps1` - Performance benchmark tool
+- **Modified**: `quickstart.ps1` - Updated import verification (2 sections)
+- **Modified**: `quickstart.sh` - Updated import verification
+
+## Performance Impact
+**Benchmark results on Windows:**
+- Before: ~19.8 seconds for import checks
+- After: ~4.9 seconds for import checks
+- **Improvement: 14.9 seconds saved (75.2% faster)**
+
+## Testing
+- ✅ All functional tests pass (`scripts/test_check_requirements.py`)
+- ✅ Quickstart scripts work correctly on Windows
+- ✅ Error handling verified (invalid imports reported correctly)
+- ✅ Performance benchmark confirms 75%+ improvement
+
+Fixes #4427

tools/src/aden_tools/tools/apify_tool/README.md

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+# Apify Tool for Hive
+
+Universal web scraping and automation through the Apify marketplace.
+
+## Overview
+
+Apify is a cloud platform providing a marketplace of thousands of ready-made web scrapers and automation tools ("Actors"). This integration allows Hive agents to extract structured data from almost any website without writing custom scraping code.
+
+## Why Use This?
+
+While agents can make raw HTTP requests, Apify interactions are complex:
+
+1. **Async Polling**: Actor runs take time (seconds to minutes). A raw request just returns a `runId`, requiring the agent to loop, sleep, and poll status—which LLMs struggle with.
+2. **Dataset Abstraction**: Fetching results requires knowing specific dataset IDs and pagination logic. This tool abstracts that into a simple `wait=True` parameter.
+3. **Security**: Keeps the `APIFY_API_TOKEN` in the credential store instead of exposing it to the agent context.
+
+## Credential Setup
+
+1. Sign up at [console.apify.com](https://console.apify.com)
+2. Go to Settings → Integrations
+3. Copy your Personal API token
+4. Set as environment variable: `export APIFY_API_TOKEN=your_token_here`
+
+## Tools
+
+### `apify_run_actor`
+
+Run an Apify Actor to scrape or automate websites.
+
+**Parameters:**
+
+- `actor_id` (str): Actor identifier (e.g., `"apify/instagram-scraper"`)
+- `input` (dict): JSON input specific to the actor (default: `{}`)
+- `wait` (bool): If `True`, waits for completion and returns results immediately. If `False`, returns `runId` for async status checks (default: `True`)
+
+**Example:**
+
+```python
+# Synchronous execution (recommended)
+result = apify_run_actor(
+    actor_id="apify/instagram-profile-scraper",
+    input={"usernames": ["instagram", "google"]},
+    wait=True
+)
+# Returns: {"items": [...], "run_id": "...", "status": "SUCCEEDED"}
+
+# Asynchronous execution
+result = apify_run_actor(
+    actor_id="apify/web-scraper",
+    input={"startUrls": [{"url": "https://example.com"}]},
+    wait=False
+)
+# Returns: {"run_id": "abc123", "status": "RUNNING"}
+```
+
+### `apify_get_dataset`
+
+Retrieve results from a completed actor run.
+
+**Parameters:**
+
+- `dataset_id` (str): Dataset identifier from a completed run
+
+**Example:**
+
+```python
+data = apify_get_dataset(dataset_id="xyz789")
+# Returns: {"items": [...], "count": 42}
+```
+
+### `apify_get_run`
+
+Check the status of an actor run.
+
+**Parameters:**
+
+- `run_id` (str): Run identifier returned from `apify_run_actor` with `wait=False`
+
+**Example:**
+
+```python
+status = apify_get_run(run_id="abc123")
+# Returns: {"status": "SUCCEEDED", "default_dataset_id": "xyz789", ...}
+```
+
+### `apify_search_actors`
+
+Search the Apify marketplace for actors (optional).
+
+**Parameters:**
+
+- `query` (str): Search keywords
+- `limit` (int): Maximum results to return (default: 10)
+
+**Example:**
+
+```python
+actors = apify_search_actors(query="instagram", limit=5)
+# Returns: {"items": [...], "total": 24}
+```
+
+## Use Cases
+
+### Lead Generation
+
+```python
+# Find email addresses of decision-makers on LinkedIn
+result = apify_run_actor(
+    actor_id="apify/linkedin-profile-scraper",
+    input={"search": "CEO at tech company in SF"},
+    wait=True
+)
+emails = [p["email"] for p in result["items"] if p.get("email")]
+```
+
+### Market Research
+
+```python
+# Monitor product prices across multiple platforms
+result = apify_run_actor(
+    actor_id="apify/amazon-scraper",
+    input={"search": "wireless headphones", "maxItems": 50},
+    wait=True
+)
+prices = [item["price"] for item in result["items"]]
+avg_price = sum(prices) / len(prices)
+```
+
+### Social Media Analytics
+
+```python
+# Analyze YouTube video comments for sentiment
+result = apify_run_actor(
+    actor_id="apify/youtube-scraper",
+    input={"videoUrls": ["https://youtube.com/watch?v=..."]},
+    wait=True
+)
+comments = result["items"][0]["comments"]
+```
+
+## Error Handling
+
+All tools return `{"error": "message", "help": "..."}` on failure:
+
+- Missing credentials
+- Invalid actor ID
+- Actor not found (404)
+- Rate limit exceeded (429)
+- Network timeouts
+- Invalid API token (401)
+
+## API Documentation
+
+- [Apify API v2](https://docs.apify.com/api/v2)
+- [Actor Marketplace](https://apify.com/store)