After publishing the previous OpenClaw hands-on review, the most common questions from comments and group chats fell into five buckets: token costs, what it can actually do, local models, privacy and security, and day-to-day experience. Today I am picking the five most frequently asked questions and answering each one in detail.
I’ve been using OpenClaw heavily on my local machine for a while now. At first, I treated it like any other AI tool. But after wiring it into Telegram, Obsidian, scheduled tasks, local models, and my content workflow, I began to see it as a system that could keep working between conversations. It can receive messages, call tools, run scheduled tasks, dispatch to different models, build long-term memory, write results back to Obsidian, and delegate complex tasks to other agents. If you’re only using it as a chatbot, you’re using only part of its capabilities.
A long main-thread Binder call can include dispatch delay, server processing, scheduling, and lock waits. This article combines Binder events, thread states, and Java monitor contention to separate those intervals.
These signals must be recorded. Sleeping or a futex stack alone does not establish a Binder or Java-lock bottleneck.
When an app misses a frame deadline, first distinguish Running, Runnable, and sleeping or blocked time. Each leads to a different investigation. This article uses CPU scheduling, frequency, idle, and sampling data to turn “the CPU is slow” into observable behavior.
Verify CPU numbering, frequency limits, and scheduling policy on the target device. Running on a smaller core alone does not establish a scheduling error.
Perfetto’s vsync-app, vsync-sf, and app doFrame tracks can look like the same event. This article follows a frame request from SurfaceFlinger scheduling to the app, then relates it to RenderThread, buffers, and FrameTimeline.
The examples mainly concern 120 Hz operation. Phase settings, hardware-callback enablement, and pending frame requests affect the tracks; separate those meanings before interpreting latency.
Version note (reviewed October 2026): Java, JNI, and scheduling code are checked against
android-16.0.0_r1; app/appSf roles also reference Android 13 source. Historical screenshots are not universal Android 16/17 configurations. Excerpts omit surrounding state where noted and come from different classes, not one compilable program.
During a scrolling slowdown, the main thread may be doing layout or may already have handed drawing work to RenderThread. This article follows their hand-off, buffer submission, and SurfaceFlinger activity in Perfetto screenshots to locate waits.
The focus is the hardware-accelerated View/HWUI path. Other engines and software drawing can use different threads. FrameTimeline and presentation-side evidence are needed to determine what reached the screen.
120 Hz reduces the nominal refresh interval from 60 Hz’s 16.67 ms to about 8.33 ms. Display refreshes, app-produced frames, and distinct frames presented are different counts. This article uses a historical Perfetto trace to explain their relationship and the rendering/power trade-offs.
Part five covered Choreographer callbacks; here the focus is the shorter display cycle. The screenshots describe that capture, not every 120 Hz device’s scheduling configuration.
This article introduces Choreographer, a class that App developers may not frequently encounter but is critically important in the Android Framework rendering pipeline. We will cover the background of its introduction, a brief overview, partial source code analysis, its interaction with MessageQueue, its application in APM (Application Performance Monitoring), and some optimization ideas for Choreographer by mobile phone manufacturers.
Choreographer coordinates pending frame callbacks with display timing; it does not itself set the screen refresh rate. At 120 Hz, the interval is about 8.33 ms. Meeting a frame deadline also depends on CPU scheduling, GPU work, buffers, and composition. Apps request callbacks as needed rather than redraw on every physical Vsync. This article also distinguishes what FrameCallback, FrameMetrics, gfxinfo, Looper, and Perfetto can observe.
This is the fourth article in the Perfetto series, explaining how to use trace_processor_shell to open large files exceeding 2GB locally. In actual problem analysis, we often encounter very large Trace files (greater than 2GB) that may fail to open in ui.perfetto.dev because of browser memory limits. The limit applies to memory used while parsing, not directly to the trace file’s size. In this case, we can use the official trace_processor_shell tool to open large files locally.
When I started this series, Perfetto had largely replaced Systrace in my daily work, and the OPPO and vivo teams I encountered were also migrating. Newcomers found the interface overwhelming and asked me to explain the subjects of my Systrace articles through Perfetto.
This is the third article in the Android App ANR series, focusing on real-world ANR cases. The series includes:
This is the second article in the Android App ANR series, focusing on ANR analysis methodology and key logs. The series includes:
This is the first article in the Android App ANR series, mainly analyzing the design philosophy of Android ANR from a system perspective. The series directory is as follows:
The first two articles covered what Perfetto is and how to capture a trace. This third article starts after you open that trace: with so much on the screen, where do you look?
Android documentation labels Systrace a legacy tool and recommends Perfetto on Android 10+. When I wrote this article, Perfetto had largely replaced Systrace in my daily work, and the OPPO and vivo teams I encountered were migrating. This series continues the earlier analysis methods with Perfetto.
Technical review: 2026-10-14. The 2024 interface and case screenshots are retained. Updates to shortcuts and analysis semantics use official documentation and v58.3 source (
11fbaed83636). The original case traces are not provided here; their illustrated wake-up chains and measurements are not new-version test results.
The previous article Android Perfetto Series 1: Introduction to Perfetto introduced what Perfetto is. This article provides a brief introduction to Perfetto capture.
Android documentation labels Systrace a legacy tool and recommends Perfetto on Android 10+. When I wrote this article, Perfetto had largely replaced Systrace in my daily work, and the OPPO and vivo teams I encountered were also migrating. This series revisits the earlier analysis methods with Perfetto.
Technical review: 2026-10-14. The main examples target Android 12+. Original 2024 screenshots remain, with older-system and newer-UI differences explained below. Commands and configuration were checked against official documentation and script source; this update adds no new device-capture results.
