Fix unscoped extension-skill removal and legacy preset provenance on direct remove

- _unregister_extension_skills(): omitting skills_dir now always triggers
  the full multi-directory fallback scan instead of narrowing to the
  currently active agent's directory. Previously, remove() (the only
  caller that omits skills_dir) would resolve the active agent's dir and
  take the scoped fast path, orphaning a previously-active second agent's
  extension skill mirror during full removal.

- PresetManager.remove(): infer legacy flat-list registered_skills
  provenance (reusing _infer_legacy_skill_provenance from the prior
  rescaffold fix) before invoking _unregister_skills, so a direct
  `preset remove` with no intervening rescaffold/switch also restores
  every previously-active agent's directory instead of only the
  currently active one.

Added regression tests:
- test_remove_while_second_agent_still_in_skills_mode_cleans_up_first_agent_mirror
- test_remove_infers_legacy_flat_list_provenance_without_prior_rescaffold

Assisted-by: GitHub Copilot (model: Claude Sonnet 5, autonomous)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

src/specify_cli/extensions/__init__.py

@@ -1241,32 +1241,32 @@ class ExtensionManager:
         Called during extension removal to clean up skill files that
         were created by ``_register_extension_skills()``.
 
-        If *skills_dir* is not provided and ``_get_skills_dir()`` returns
-        ``None`` (e.g. the user removed init-options.json or toggled
-        ai_skills after installation), we fall back to scanning all known
-        agent skills directories so that orphaned skill directories are
-        still cleaned up.  In that case each candidate directory is
-        verified against the SKILL.md ``metadata.source`` field before
-        removal to avoid accidentally deleting user-created skills with
-        the same name.
+        When *skills_dir* is omitted, this is a genuinely unscoped removal
+        (e.g. full extension removal): ``registered_skills`` is a single
+        flat list covering mirrors created under *every* agent this
+        extension was ever activated under, not just the currently active
+        one, so we always scan all known agent skills directories rather
+        than narrowing to whichever agent happens to be active right now.
+        Each candidate directory is verified against the SKILL.md
+        ``metadata.source`` field before removal to avoid accidentally
+        deleting user-created skills with the same name.
 
         Args:
             skill_names: List of skill names to remove.
             extension_id: Extension ID used to verify ownership during
                 fallback candidate scanning.
-            skills_dir: Optional explicit skills directory to use instead
-                of resolving via ``_get_skills_dir()``.  Useful when the
-                caller needs to target a specific agent's skills directory
-                regardless of the currently-active agent in init-options.
+            skills_dir: Optional explicit skills directory to scope
+                cleanup to. Useful when the caller needs to target a
+                specific agent's skills directory regardless of the
+                currently-active agent in init-options. When omitted,
+                every configured agent's skills directory is scanned
+                instead of resolving just the currently active one.
         """
         if not skill_names:
             return
 
         from ..shared_infra import _validate_safe_shared_directory
 
-        if skills_dir is None:
-            skills_dir = self._get_skills_dir()
-
         if skills_dir:
             # Reject the candidate directory itself (any path component,
             # including the final one) if it's a symlink escaping the

src/specify_cli/presets/__init__.py

@@ -2247,6 +2247,30 @@ class PresetManager:
         metadata = self.registry.get(pack_id)
         # Restore original skills when preset is removed
         registered_skills = metadata.get("registered_skills", []) if metadata else []
+        if isinstance(registered_skills, list) and registered_skills:
+            # Legacy flat-list registries predate per-agent provenance
+            # tracking. Migration to the per-agent dict form previously
+            # only happened during a rescaffold (register_enabled_presets_
+            # for_agent); if the *first* post-upgrade operation is instead
+            # `preset remove` (no intervening use/upgrade), the legacy
+            # branch of _unregister_skills restores only the currently
+            # active agent's directory, leaving this preset's overrides in
+            # every previously active agent's directory orphaned. Infer
+            # real per-agent ownership from the on-disk preset marker now,
+            # while pack_id is still known, and hand the resulting mapping
+            # through the same dict-based cleanup path already used for
+            # non-legacy registries (#2948).
+            from .. import load_init_options
+
+            init_opts = load_init_options(self.project_root)
+            fallback_agent = init_opts.get("ai") if isinstance(init_opts, dict) else None
+            if not isinstance(fallback_agent, str):
+                fallback_agent = ""
+            registered_skills = self._infer_legacy_skill_provenance(
+                [name for name in registered_skills if isinstance(name, str)],
+                pack_id,
+                fallback_agent=fallback_agent,
+            )
         registered_commands = metadata.get("registered_commands", {}) if metadata else {}
         pack_dir = self.presets_dir / pack_id