Love the concept! Some feedback: I went to sign up to give it a go, but the set up process left me feeling a bit untrusting - so I backed out for now. I'd prefer more explanation about what to expect, what I will get, how it is safe, etc before asking me to run a prompt.

Thank you! Very good point.

Right now, the prompt will enumerate all the services and install the OpenTelemetry SDK (https://opentelemetry.io/) in each service.

Then for every service, the skill will make sure that:

- Every time something breaks and an operator needs to take a look, there's an error log - All important steps in a process emit info/debug logs (so that an issue can be investigated) - Operations are covered with spans with relevant attributes. - Cost (LLM tokens), API performance (latency/RED), tenant activity (cost/usage per tenant) are covered by metrics so that you can use Superlog MCP to build cool dashboards.

For most common stacks like NextJS, FastAPI, React Native/Expo etc. we have a custom skill that explains the best practices for this specific technology. For all the other stacks we ask the agent to use general best practices.

We have evals for all custom skills where we start from a starter project, run the agent with the skill and use LLM-as-a-judge to compare it to a human-written 'golden patch'.

In general, we try to:

- minimize diff, so that the instrumentation is easy to review - make small chunks of additive diffs vs huge indents / moving logic around - minimize new dependencies - use well-supported and audited OTel SDKs vs custom libs

You can read the skills here: https://github.com/superloglabs/skills.

I'll make sure to add this to our landing and print this out as the agent writes the code!

Thank you for the feedback!