dia-source-analysis
GitHub用于逆向分析Dia浏览器内部架构,提取Bun/TS代理代码及映射AI代理、沙箱与本地ML设计。适用于研究其工作原理或对比termio方案,仅限只读学习,禁止复制分发。
Trigger Scenarios
Install
npx skills add termio-sh/termio --skill dia-source-analysis -g -y
SKILL.md
Frontmatter
{
"name": "dia-source-analysis",
"description": "Analyze \/ reverse-engineer the locally installed Dia Browser mac app (The Browser Company; bundle id company.thebrowser.dia; shares ArcCore with Arc). Inspect its app bundle, extract its Bun\/TypeScript agent-server source from shipped source maps, fingerprint the runtime, read native-Swift symbols, and map its AI-agent \/ sandbox \/ on-device-ML architecture. Invoke when the user wants to study how Dia works internally, extract Dia's agent code, or compare Dia's agent\/terminal approach against termio. (User sometimes voice-types the name as 'DotBrowser' — same app.)"
}
Analyze Dia Browser source
Dia (/Applications/Dia.app, The Browser Company, company.thebrowser.dia) is a
WebKit-based browser (~1.4 GB) that shares ArcCore.framework with Arc. termio uses
it as a reference for how a shipping product drives AI coding agents as sandboxed
child processes (Dia shells to the real Claude Code CLI under Seatbelt) and for its
agent-server / IPC architecture. This skill captures how to dig into it and what's
already known, so analysis doesn't start from scratch each time.
Golden rules
- Read-only, on the user's own machine, for research. This is proprietary code shipped to the user. Use it to understand and learn, never to copy/redistribute verbatim or ship lifted code. State this caveat when sharing recovered source.
- Verify before trusting old findings. The "Established facts" below are version-stamped.
Dia auto-updates (Sparkle); bundle layout, file hashes, runtime versions, and even whether
source maps ship can all change. Always re-read
info.json+CFBundleShortVersionStringfirst and treat mismatches as "re-derive from scratch." - Two recoverability tiers: the Bun/TS agent backend is near-fully recoverable (source maps); the native Swift app is symbols/structure only (no real source).
Established facts (as of Dia 1.34.2 — RE-VERIFY)
Agent-server info.json (1.34.2): version 1.0.0, buildDate 2026-06-10, commit 47de9fbe6c4,
claudeCodeVersion 2.1.131. (Was 1.32.0 / commit 55d9d2e174b / buildDate 2026-05-20.)
- ⚠️ Source maps NO LONGER SHIP as of 1.34.2.
extract-sourcemaps.pyreturns "No .map files found" — the Bun/TS agent-server backend is no longer recoverable as near-original TS (only logic compiled into the Mach-O remains). The native-Swift tier is unchanged: symbols + embedded source paths only. So "the big win" in §1 below is gone on current builds; keep the procedure for older installs / in case they return. - Agent backend = Bun-compiled standalone Mach-O (
agent-server,handler) + the real Claude Code CLI (claude, 206 MB, itself a Bun binary). No separate Node/Bun runtime is installed — each binary embeds Bun. They run as child processes under Seatbelt sandbox (sandbox-exec -f agent.sb/agent-claude-code.sb, params via-D DATA_DIR=…), talking to the native UI over SSE/IPC (transport/sse.ts,ipc-gateway.ts). Per-context workspace atdata/contexts/{contextId}with resumable disk buffers (session/buffer.ts, JSONL). This is the part most relevant to termio — termio runs agents in real PTYs (.exec) instead, but the child-process-under-sandbox + resumable-buffer + IPC design is the directly comparable bit. - Streaming smoothness comes from native rendering +
session/update-batcher.ts: deltas are coalesced and flushed only on ≥256 B OR 250 ms idle OR completion — so the UI updates a few times/sec, not per token. The Bun agent-server is backend orchestration and does NOT touch UI perf. - AI chat ("AssistantPanel") renders NATIVELY, not in a webview. Markdown parsed by
cmark(swift-markdown), code highlighted by Highlightr (CodeAttributedString→ NSAttributedString), math by SwiftMath (MTMathListDisplay, CoreText). UI is AppKitNSViewControllers (source pathsFrameworks/BoostBrowser/Sources/AssistantPanel/*.swift). - The AI input is the native AppKit module
BoostCommandBar(Frameworks/BoostBrowser/ Sources/BoostCommandBar/*): a token/pillTokenTextVieww/SkillPillTokenViewProvider; Skills =SkillsV3;@-mentions (AtMentionKeywords: @Search/@Slack/@Gmail/@Notion) insert context/tool pills. On-devicecmd_t_router(3-label intent) +skillsclassifier rank proactive suggestions. - WKWebView (~45 refs) is for web pages + HTML "artifacts" (reports/slides via
report-kit/slide-kit), NOT for chat bubbles. - On-device ML (
OnDeviceLoRAadaptorsbundle, 152 M): one shared DistilBERT-base encoder (126 M, fp16) + three LoRA adapters + heads —cmd_t_router(input intent),skills(which skill to fire),sensitive_content(privacy gate). Run via MLX (mlx-swift).
Bundle map
| Path | Size | What |
|---|---|---|
Contents/Frameworks/ArcCore.framework |
~548 M | browser engine core (WebKit + Arc) |
Contents/Resources/agent-server-resources/dist |
~371 M | Bun agent backend + bundled claude CLI (206 M) |
Contents/Resources/OnDeviceLoRAadaptors_…bundle |
~152 M | DistilBERT base + 3 LoRA classifiers |
Contents/MacOS/Dia |
~106 M | native Swift app binary (AssistantPanel etc.) |
Contents/Frameworks/libAIInfra.dylib |
~21 M | on-device classification (LocalClassification) |
Contents/Resources/*.bundle |
— | Highlightr, SwiftMath, SwiftProtobuf, mlx-swift, swift-transformers, ARC/BoostBrowser feature bundles |
dist/*.sb |
— | Seatbelt sandbox profiles |
Procedure
0. Identify version (always first)
/usr/libexec/PlistBuddy -c "Print :CFBundleShortVersionString" /Applications/Dia.app/Contents/Info.plist
cat "/Applications/Dia.app/Contents/Resources/agent-server-resources/dist/info.json"
1. Recover the agent-server source (the big win)
The .js bundles are compiled into the Mach-O binaries and NOT shipped, but entrypoint.js.map
and handler-entrypoint.js.map ship with sourcesContent populated → near-original TS.
python3 skills/dia-source-analysis/scripts/extract-sourcemaps.py --out /tmp/dia-src
Yields ~40 "own" TS files (non-node_modules): agent/harness/claude-sdk/* (how it drives the
Claude SDK — prompt-template.ts, proxy-tools.ts, claude-sdk-in-process.ts, sandbox.ts),
session/*, transport/*, handler/*, runtime.ts, watchdog.ts, main.ts. Also readable
without extraction: dist/agents/*/spec.yaml, dist/agents/*/.claude/, dist/resources/tool-schemas/*.json.
2. Fingerprint the runtime
D=/Applications/Dia.app/Contents/Resources/agent-server-resources/dist
for f in agent-server handler claude; do echo "== $f"; \
strings -a "$D/$f" | grep -iE "Bun v[0-9]|Bun/[0-9]|node\.js v[0-9]"|sort -u|head; done
3. Native Swift binary — structure recoverable via ipsw class-dump --swift (no bodies)
The symbol table is stripped (nm ≈ 8.5k symbols, no Swift method-body symbols; debugger
attach is blocked by hardened runtime flags=0x10000(runtime) + no get-task-allow). But the
Swift reflection metadata survives and gives field-level structure — the closest thing to source:
brew install ipsw # one-time
BIN=/Applications/Dia.app/Contents/MacOS/Dia
strings -a "$BIN" | grep -iE "AssistantPanel|Highlightr|SwiftMath|cmark|MarkdownText" | sort -u | head
ipsw class-dump "$BIN" --class 'AssistantPanel' # response/content view controllers
ipsw macho info "$BIN" --swift-all | grep -i <Type> # generics
This yields class/struct instance-variable layouts, superclasses, protocol conformances, and
method signatures — NOT bodies, and NOT the numeric values of fields. strings still gives
demangled type names + embedded source paths (/Users/admin/actions-runner/_work/arc/arc/…).
For deeper work use Hopper/Ghidra, but Swift ABI makes UI/animation bodies near-unreadable.
4. On-device models
B=/Applications/Dia.app/Contents/Resources/OnDeviceLoRAadaptors_OnDeviceLoRAadaptors.bundle/Contents/Resources
cat "$B/config.json"; ls -lhS "$B"/*.safetensors
strings -a /Applications/Dia.app/Contents/Frameworks/libAIInfra.dylib | grep -iE "cmd_t|router|sensitive|skills_|distilbert|lora" | sort -u | head
5. Sandbox profiles (most relevant to termio)
cat /Applications/Dia.app/Contents/Resources/agent-server-resources/dist/agent.sb
cat /Applications/Dia.app/Contents/Resources/agent-server-resources/dist/agent-claude-code.sb
These are Seatbelt (sandbox-exec) profiles — read them to see exactly what the agent / Claude
Code subprocess may touch.
Relevance to termio
termio is a native Swift + libghostty terminal for AI coding agents (unpeel-style): it runs
each agent/session in a real PTY (.exec) via a libghostty surface, unsandboxed. Dia solves an
adjacent problem — driving the same Claude Code CLI — but from a browser, sandboxed, over IPC.
When comparing, borrow narrowly (termio is deliberately simple/minimal — do not import Dia's
~370 M Bun agent-server, on-device ML stack, or browser surface):
- Sandbox profiles (§5) are the highest-value takeaway: if termio ever wants to constrain
what an agent session can touch beyond the PTY, Dia's
agent.sb/agent-claude-code.sbSeatbelt profiles are a concrete, shipping reference forsandbox-exec. - Child-process + resumable buffer + IPC design (
session/buffer.tsJSONL, per-context workspace) is the architecture analog to termio keeping aTerminalControlleralive per session in the SurfaceCache — same goal (survive view rebuilds / resume), different mechanism. - Delta coalescing (
update-batcher.ts: flush on ≥256 B / 250 ms idle / completion) is a generic perf lesson if termio ever renders agent output outside the raw terminal grid. - Skip: the native AssistantPanel renderer and on-device LoRA classifiers — termio shows a real terminal, not a native chat surface, so those don't map.
Version History
-
2dfed32
Current 2026-08-27 09:02
Dia 1.34.2 版本已不再提供源映射文件,Bun/TS agent-server 后端无法再按原样恢复源码,仅保留 Mach-O 逻辑和 Swift 符号结构。


