@vida_agent: We open-sourced BrowserBC: A system that turns human browser trajectories into reusable agent skills. Just one recordin…
Summary
BrowserBC is an open-source system that converts recorded human browser interactions into reusable agent skills, enabling skills to be used in Claude Desktop and Claude Code with just one recording.
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Cached at: 06/28/26, 03:55 AM
We open-sourced BrowserBC: A system that turns human browser trajectories into reusable agent skills. Just one recording is enough to generalize a skill.
🛠️ GitHub: [https://t.co/OHhHMzQJ1W]
Here’s how it works. 👇 https://t.co/r1qpsPZLqQ
Einsia/Browser-BC
Source: https://github.com/Einsia/Browser-BC
Journey Forge Local
Record your own browser tasks → each website accumulates a bucket of capabilities, and every capability distills into one reusable skill → use them in Claude Desktop (and Claude Code). A single-user, local product. You bring your own LLM API key. Pure Python at runtime (no Node needed). Not a benchmark.
extension (record free-form task)
└─► localhost server :8099 /v1/traces/init → chunks → finalize
└─ assemble → data/traces/<id>/trace.json (intent + events)
└─ background harness pipeline:
atomize → classify (capability) → bucket (per domain+capability)
→ distill bucket → SKILL.md + TRACE_GUIDE.md → install
├─ Claude Code: ~/.claude/skills/<domain>-<capability>/SKILL.md (auto)
└─ Claude Desktop: <name>.zip → upload via Settings → Skills
/api/buckets exposes per-site capability buckets + skills
Each website is a folder of capability buckets, e.g.
github.com/{login-with-credentials, signup-with-email, …} — a new recording is
atomized into segments, each segment classified into a capability, and segments
of the same capability pooled into one bucket that distills into one skill.
Layout
| Path | What |
|---|---|
entry/main.py | Desktop entry — starts the server, opens the panel in your browser |
app/dist/index.html | Control panel (zero-build, served by the server) |
extension/ | The recorder (product fork: points at localhost, free-form only) |
server/server.py | Local ingestion + control API |
harness/ | Distillation pipeline: atomize / classify / bucket / distill / install (pure Python) |
harness/main.py | CLI: ingest / distill / status / consolidate / query |
scripts/start.sh | Headless dev launcher |
docs/ | Trace schema + Claude Desktop setup |
State lives under data/harness/: buckets.json, registry.json, and
skills/<domain>/<capability>/{SKILL.md,TRACE_GUIDE.md,meta.json,evidence.jsonl}.
Quick start
-
Configure & run the server
cp config.example.env .env.local # then set SF_LLM_KEY=sk-ant-... ./scripts/start.sh # or: python entry/main.py (native window)The panel is at http://127.0.0.1:8099/. The server seeds a default key (
jfl-local-dev-key) the extension ships with, so it connects automatically. -
Build & load the extension
cd extension && pnpm install && pnpm buildChrome →
chrome://extensions→ enable Developer mode → Load unpacked → selectextension/dist/chrome-mv3. It’s pre-pointed at the local server. -
Record → finalize. Record a short task with the extension, stop, label, upload. With auto-distill on, a skill appears within ~1–3 min:
- Claude Code: already installed under your skills root.
- Claude Desktop: download the
.zipfrom the panel (Trajectories) and upload it in Settings → Skills. Seedocs/claude-desktop-setup.md.
-
(Optional) real browser execution. Panel → Browser execution → Configure Playwright MCP so Claude Desktop can actually click/type/navigate. Restart Claude Desktop after.
Notes
- Skills don’t grant tools. A
SKILL.mdis injected instructions. To execute its steps in a browser you must configure a browser MCP (Playwright) separately — the panel automates this for Claude Desktop. - LLM: the distiller speaks the Anthropic Messages API natively (default
claude-opus-4-8). PointSF_LLM_BASEat an OpenAI-compatible gateway to use that path instead. - Data lives under
data/(git-ignored). Nothing leaves your machine except the distillation calls to your configured LLM.
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