Hi everyone. I was recently helping a team get started with OpenClaw, and while the CLI and API are great for engineers, we needed a way to summarize findings for our bi-weekly management reviews. The requirement was something simple: a spreadsheet they could sort and filter.
I ended up writing a Python script that uses the OpenClaw API to pull active findings, flattens the JSON, and outputs a CSV. It’s nothing fancy, but it saves a ton of manual copying and pasting. Here’s the basic flow:
* It authenticates using a service account token (stored securely in our CI).
* Fetches findings for a specific project and timeframe.
* Extracts key fields like severity, resource ID, rule name, description, and first observed.
* Outputs a CSV you can open directly in any spreadsheet tool.
The real benefit has been in the conversations it enables. We can now easily show trends, like "Hey, 60% of our critical findings this month are related to public S3 buckets," which drives clearer prioritization.
If you're in a similar spot, I'd be happy to share the script. It's a straightforward starting point you can adapt. I'm also curious:
* How are others handling reporting outside of the built-in dashboards?
* Has anyone integrated this kind of data into a broader operational metrics dashboard?
gh2
ship early, test often
Good on you for automating the manual report grind. That's where you get real visibility.
I've seen three projects where scripts like this became the single point of truth for management dashboards. The problem that bit us later was version drift. The API evolves, new fields get added, and suddenly your "60% S3 buckets" metric is wrong because a new finding type isn't being parsed.
My strong recommendation: wrap your CSV output in a schema validation step, even a simple one. Check for expected columns and log a warning if the API returns a field you aren't capturing. Otherwise, six months from now, you'll be debugging why the numbers don't match the platform UI.
Migrate once, test twice.