git:20260902.af2a47c to git:20260906.f9cef19

+ description: Identify outstanding LinkedIn profiles, import manually retrieved JSON and diagnose registry/cache state. Use for the manual profile-retrieval workflow.

+ # LinkedIn maintenance

+ Reconcile manual LinkedIn retrieval with dataset caches and the shared registry.

+ ## Operations and effects

+

+ - `missing`: read rosters from active startup/community datasets and call the

+ resolver with `allow_scrape=False`. It can register missing profiles or

+ reconcile cached state; it is not read-only. Print distinct URLs for open/failed

+ registry entries. Missing or malformed rosters can abort the scan.

+ - `import`: read one JSON object or an array. Write cleaned profile JSON through

+ `LinkedInProfileStore` to registered datasets and an optional explicit dataset,

+ then remove resolved registry identities. Provider error/not-found records

+ update registry status. Invalid/unidentified entries or entries without a

+ target are skipped; writes already completed can remain after a later error.

+ - `diagnose`: report registry entries and missing/cached datasets without fetching

+ profiles or writing changes.

+

+ `lib.people.linkedin.maintenance` owns import and diagnostic behavior. These

+ operations do not generate person profiles or edit the manual roster. There is

+ no harness command or bulk-refresh registration.

+

+ ## Usage

+

+ conda run -n sictic-env python -m skills.linkedin_maintenance missing

+ conda run -n sictic-env python -m skills.linkedin_maintenance import profiles.json --dataset sictic-members

+ conda run -n sictic-env python -m skills.linkedin_maintenance diagnose

+

+ ## References

+

+ - [Workflow adapter](maintenance.py), [CLI](__main__.py)

+ - [Shared import and diagnostics](../../lib/people/linkedin/maintenance.py)

+ - [LinkedIn persistence contracts](../standards_and_architecture/SKILL.md#linkedin-retrieval-and-persistence)