skill-feedback

You can log local skill usage feedback without sending telemetry by running a CLI command to append an entry with your rating and outcome to a local per-skill JSONL file.

Privacy-preserving usage logging works by storing feedback data strictly in local storage files, ensuring absolutely no network calls or telemetry leave your machine unless you explicitly run a submit command.

You generate an aggregate report from local skill feedback logs by executing a report command, which reads the append-only local JSONL files and aggregates the stored usage data.

Yes, you can submit local usage logs to a GitHub issue from the command line by running a submit command that bundles your locally stored feedback entries into a formatted issue body for the upstream repository.

Yes, local-first self-assessment is suitable for measuring team skill effectiveness because developers can log outcomes and friction locally, then aggregate the data to review effectiveness without forced telemetry.

The main limitation of local storage for skill feedback logging is that data remains siloed on each individual machine until a user explicitly executes a submit command to bundle entries upstream.