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feat(onboarding): recommend plugins and skills from installed apps (#109668)

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* feat(onboarding): recommend plugins and skills from installed apps

Scan installed macOS apps during classic onboarding (TCC-free), gather
candidates from official catalogs + ClawHub search, let the configured
model pick genuine matches, and offer an opt-in multiselect install step.
Adds a device.apps node-host command (default-off sharing, Android-parity
envelope) so remote gateways can request a paired Mac's inventory, and a
wizard.appRecommendations kill switch. Custom setup-inference completions
no longer inherit the 32-token verification-probe output cap.

* feat(onboarding): recommend apps in guided flow

* fix(onboarding): harden app recommendations against ClawHub self-promotion

Third-party ClawHub skills are never pre-selected regardless of model tier
(publisher-controlled listing text reaches the matcher prompt and could
promote itself); their labels now say they install third-party code.
Installed-app scans follow symlinked .app bundles. Matcher output stays
bounded by the resolved model's own maxTokens budget (documented invariant).

* fix(onboarding): key official catalog candidates by resolved plugin id

Real catalog entries are package manifests without a top-level id; keying the
candidate map and channel/provider classification by entry.id collapsed the
whole official catalog into one undefined-keyed entry, so no official plugin
or channel was ever recommended. Regression test runs against the bundled
catalogs.

* fix(onboarding): satisfy lint, types, deadcode, and migration gates

Split the guided-onboarding test into a self-contained custodian suite to stay
under max-lines. Narrow app-recommendation exports (drop dead node-payload
normalizer, unexport internal types/helpers, route candidate tests through the
public API), replace map-spread with a helper, unexport device.apps result
types, add installedAppsSharing to node-host migration expectations, cast the
wizard multiselect mock, and regenerate the docs map.

* test(onboarding): register new live test in the shard classifier
This commit is contained in:
Peter Steinberger
2026-07-17 14:07:59 +01:00
committed by GitHub
parent 8020dd3e08
commit da69daeb72
47 changed files with 2323 additions and 192 deletions
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7
docs/cli/onboard.md
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@@ -102,8 +102,11 @@ wizard shows the same page after it prepares the workspace.
After inference passes (and the memory-import offer), guided onboarding
applies the standard setup automatically — workspace, Gateway, and sessions,
the same plan the conversational `openclaw setup` chat would apply on "yes" —
announces where to find OpenClaw later, and hatches your agent directly in the
terminal chat. If applying setup fails, onboarding falls back to the
then offers plugin and skill recommendations from installed apps; app names
are matched through your configured model and ClawHub search, and the step can
be disabled with [`wizard.appRecommendations`](/gateway/configuration-reference#wizard).
It then announces where to find OpenClaw later and hatches your agent directly
in the terminal chat. If applying setup fails, onboarding falls back to the
conversational OpenClaw chat to finish interactively. Channels, agents,
plugins, and other optional features remain OpenClaw chat territory: run
`openclaw` and use `open channel wizard for <channel>` to hand channel