helpme-ng: python (originally?) oriented library for common functionality

Increasingly often I wish I had a library which I could have used across projects with minimal scaffolding and which provided functionality absorbing

- **collect info for troubleshooting**: `datalad wtf` -- collection/presentation of relevant information about system, dependencies, configuration
- **auto-collect info while running tests**: a quick summary for running tests so later it is easier to deduce (e.g. from con/tinuous collected logs) on what differed.
- could be the same `wtf` like we do in DataLad CI
- could be quick generic (not needing much of parametrization besides package name) pytest fixture like we made for dandi-cli: https://github.com/dandi/dandi-cli/blob/master/dandi/pytest_plugin.py#L38
- **helper to file an issue**: @vsoch's https://vsoch.github.io/helpme/ for which she bootstrapped https://github.com/datalad/datalad-helpme
- ideally should respect also potentially available in the project/repo issue template (under known locations like .github/)
- should be easy to attach to overall exception handler where it would do its job
- even better might be integrated within wrappers like con-duct (attn @asmacdo) where upon abnormal exit, could deduce python package to collect info about, research on where source code hosted (e.g. via source record on pypi) and also proceed to file an issue (`con-duct run --on-error file-issue`)
- there we had discussions on trying to fingerprint python tracebacks so we could actually identify already filed issues with the same traceback and alike. Now it could be offloaded potentially/optionally to some LLM.

@con/developers @con/centroids @con/Collaborators may be you saw/know of such a library or efforts to learn from?

Start by reading the linked dandi pytest_plugin.py and datalad-helpme project, then inspect the referenced .github issue-template locations and con-duct's `run --on-error file-issue` entry point. Done requires narrowing these ideas into a defined library scope and an agreed initial feature set.

Written by the indexing model from the issue text.