control-camera-regression-review

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Aktualisiert15. März 2026 um 18:11

Review regression-sensitive LawnBerry Pi manual control and camera paths: RoboHAT USB handoff, watchdog feeding, motor authorization, joystick responsiveness, MJPEG and snapshot fallback, camera ownership, and stream backpressure handling.

Installation

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Quelle

acredsfan

acredsfan/lawnberry_pi

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Verwandte BerufeSOC

Basierend auf der SOC-Berufsklassifikation

Softwarequalitätssicherungsanalysten und -testerInformatik- und Mathematikberufe·SOC 15-1253

SKILL.md

readonly

name	control-camera-regression-review
description	Review regression-sensitive LawnBerry Pi manual control and camera paths: RoboHAT USB handoff, watchdog feeding, motor authorization, joystick responsiveness, MJPEG and snapshot fallback, camera ownership, and stream backpressure handling.
argument-hint	What manual-control or camera change should be reviewed or hardened?
user-invocable	true

Control and Camera Regression Review

What this skill does

This skill provides a conservative review workflow for the two highest-regression surfaces called out in the maintainer handbook: manual control and camera streaming.

Read first

docs/developer-toolkit.md
docs/RELEASE_NOTES.md
backend/src/services/robohat_service.py
backend/src/services/camera_stream_service.py
relevant frontend control/camera views, stores, and services
focused tests for RoboHAT and camera streaming

Review procedure

Identify whether the change touches drive control, USB control handoff, blade-related UI coupling, live stream delivery, snapshots, or operator responsiveness.
Trace the backend path end to end.
- control commands and safety gates
- watchdog heartbeat feeding
- motor authorization and interlock checks
- RoboHAT RC vs USB ownership behavior
- camera backend selection, simulation fallback, and client delivery path
Trace the frontend/operator path.
- rate or debounce behavior
- API and WebSocket interaction
- reconnect or fallback handling
- user-visible fault states
Review tests before refactoring and extend focused coverage instead of relying on happy-path smoke tests.
Validate in simulation-safe mode first.

Non-negotiable checks

control changes fail closed when safety state is uncertain
USB control loss does not get hand-waved away as transient noise
camera changes respect centralized device ownership
fallback behavior is explicit, not accidental
performance or responsiveness claims are backed by actual targeted checks from this session

Completion checks

changed control/camera path was traced across API, services, and UI if applicable
regression tests exist or were updated near the sensitive seam
the summary calls out any remaining hardware-sensitive risk clearly

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name	control-camera-regression-review
description	Review regression-sensitive LawnBerry Pi manual control and camera paths: RoboHAT USB handoff, watchdog feeding, motor authorization, joystick responsiveness, MJPEG and snapshot fallback, camera ownership, and stream backpressure handling.
argument-hint	What manual-control or camera change should be reviewed or hardened?
user-invocable	true

Control and Camera Regression Review

What this skill does

This skill provides a conservative review workflow for the two highest-regression surfaces called out in the maintainer handbook: manual control and camera streaming.

Read first

docs/developer-toolkit.md
docs/RELEASE_NOTES.md
backend/src/services/robohat_service.py
backend/src/services/camera_stream_service.py
relevant frontend control/camera views, stores, and services
focused tests for RoboHAT and camera streaming

Review procedure

Identify whether the change touches drive control, USB control handoff, blade-related UI coupling, live stream delivery, snapshots, or operator responsiveness.
Trace the backend path end to end.
- control commands and safety gates
- watchdog heartbeat feeding
- motor authorization and interlock checks
- RoboHAT RC vs USB ownership behavior
- camera backend selection, simulation fallback, and client delivery path
Trace the frontend/operator path.
- rate or debounce behavior
- API and WebSocket interaction
- reconnect or fallback handling
- user-visible fault states
Review tests before refactoring and extend focused coverage instead of relying on happy-path smoke tests.
Validate in simulation-safe mode first.

Non-negotiable checks

control changes fail closed when safety state is uncertain
USB control loss does not get hand-waved away as transient noise
camera changes respect centralized device ownership
fallback behavior is explicit, not accidental
performance or responsiveness claims are backed by actual targeted checks from this session

Completion checks

changed control/camera path was traced across API, services, and UI if applicable
regression tests exist or were updated near the sensitive seam
the summary calls out any remaining hardware-sensitive risk clearly