> ## Documentation Index
> Fetch the complete documentation index at: https://docs.sentrion.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Best Practices

> Tips and recommendations for getting the most out of Sentrion

# Best Practices

Follow these recommendations to get the most out of the Sentrion API.

## Efficient API Usage

### Use specific filters

The more specific your search, the faster and more relevant your results. Combine multiple filters to narrow down results:

```json theme={null}
{
  "company_name": "Stripe",
  "country": "United States",
  "department": "Engineering",
  "seniority": "Senior"
}
```

### Paginate large result sets

Use cursor-based pagination to efficiently retrieve large datasets without hitting rate limits:

```python theme={null}
cursor = None
all_jobs = []

while True:
    response = search_jobs(company_name="Google", cursor=cursor)
    all_jobs.extend(response["jobs"])

    cursor = response.get("next_cursor")
    if not cursor:
        break
```

### Monitor your credit usage

Each API response includes credit tracking fields. Monitor these to stay within your plan limits:

```json theme={null}
{
  "credits_used": 1,
  "credits_remaining": 499
}
```

## Data Freshness

* Use date filters (`date_posted_after`, `date_posted_before`) to focus on recent postings.
* Job postings can be removed or filled quickly — build your workflows to handle missing listings gracefully.

## Rate Limiting

* Respect rate limits to avoid throttling.
* Implement exponential backoff for retries.
* Cache results when possible to reduce unnecessary API calls.