Zhangluo: Open-Web Fiduciary Browser Agent

Open-source browser-native fiduciary agent on standard HTML5/JS. Exposes .well-known/agent.json & WebMCP tools while keeping medical PII in window.ai (0 cloud bytes) & preventing duplicate buys.

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Zhangluo (小張羅): Fiduciary Browser Agent & Consent-Gated Open Agentic Commerce

0:00 - 0:28 ⚡ The 30-Second Aha Moment (Judge Video & Live Browser Guide)

  • 🌐 Live Open-Web Browser Agent (HTML5/JS + WebMCP + window.ai): https://gobuildrun.github.io/zhangluo-global-agent/?mode=agentic-web
  • 📜 Live Machine-Discoverable Manifest (/.well-known/agent.json): https://gobuildrun.github.io/zhangluo-global-agent/.well-known/agent.json
  • 🎥 1m48s 1080p English Demo Video: https://youtu.be/1wwW4HmMAUA
    • 0:00 - 0:28 ⚡ The 30-Second Aha Moment: User runs a 12-second camera sweep (750ms keyframe diff >= 0.035) across a crowded closet; Zhangluo indexes items locally and intercepts a duplicate 65L storage box purchase before checkout (-$19.50 saved).
    • 0:29 - 0:58 🧭 Anti-Paid-Ad Merchant & Provenance Verification: Enforces >= 10 yr operating longevity, <= 2 branches, and National GI standards (0% Ad Boost).
    • 0:59 - 1:25 🧠 On-Device Browser Privacy Gate & OpenViking Consent Memory: Medical redlines (gout purine limits, prescriptions, peanut anaphylaxis) execute 100% inside the browser/device runtime (0 bytes leaked to external servers) while inferred preferences require a user-signed consent_id.
    • 1:26 - 1:48 🔐 Cryptographic comparison_digest & Fiduciary Settlement: Emits a tamper-evident SHA-256 comparison digest before user-authorized settlement and writes receipts back to Home Inventory.

1. Inspiration: Why the Open Agentic Web Needs User-Controlled Fiduciary Boundaries

As websites evolve from human-only pages into machine-callable endpoints, two structural failures threaten an open web of agents:

  1. Closed-Silo Context Leakage: Proprietary cloud assistants stream raw household camera sweeps, medical allergies, and family calendars into vendor silos without granular consent.
  2. Ad-Biased Shopping Bots: Commercial agents optimize for affiliate commissions and paid rankings rather than checking whether the household already owns the item.

We built Zhangluo (小張羅 — "The Season-Wise Fiduciary Steward"), a 100% MIT open-source, browser-native Fiduciary Agent & Agentic Website built directly on standard web technologies (HTML5, ES2022 JavaScript, HTTP JSON-RPC 2.0, navigator.modelContext WebMCP, and window.ai on-device Web AI). It demonstrates how user-controlled browser agents and open-web services can discover capabilities, enforce cryptographic consent, and collaborate across the web without platform lock-in.

2. Open Agentic Web Architecture (HTML/JS + WebMCP + .well-known/agent.json)

A. Open-Web Discovery (/.well-known/agent.json & <link rel="agent-manifest">)

  • Publishes a machine-readable Open Agentic Web (open-agentic-web-nanda-webmcp/v1) capability manifest (urn:nanda:gobuildrun:zhangluo-fiduciary-browser-agent) linked directly in HTML <head> (<link rel="agent-manifest" href="./.well-known/agent.json" />).
  • Any external agent, MIT NANDA portable runtime, Cognizant Neuro SAN multi-agent network, or Mozilla Otari router can discover Zhangluo's trust guarantees and JSON Schemas over plain HTTPS with zero proprietary SDKs.

B. Dual-Surface WebMCP Tool Bus (navigator.modelContext + POST /api/webmcp)

Exposes three deterministic fiduciary tools both in-browser (navigator.modelContext.registerTool & window.__WEBMCP_AGENT__) and via JSON-RPC 2.0 HTTP (POST /api/webmcp):

  1. check_duplicate_inventory: Cross-checks requested items against the user's 4-pillar Household Inventory (起居簿·家当) before checkout, preventing duplicate purchases ($19.50 saved on existing closet stock).
  2. verify_merchant_purity: Evaluates open-web goods against deterministic anti-slop rules (>= 10 yr longevity, <= 2 branches, GB/T 20560 GI registry) with 0.0% paid ad boost and returns a SHA-256 comparison_digest.
  3. request_consent_memory: Enforces Consent-Gated Portable Memory (OpenViking consent_id)—external websites and peer agents can propose preferences into a pending inbox, but can never mutate active profile state without user approval.

C. User-Controlled Browser Runtime (window.ai Edge Privacy Router)

  • Zero-Cloud-Byte Medical Gate (firebase_hybrid_ai.py + index.html): Sensitive keywords (gout, purine, colchicine, peanut, allergy, camera_sweep) force execution onto the browser's local window.ai Gemini Nano runtime (0 bytes sent over the network), with full Airplane Mode (SIMULATE_OFFLINE) resilience.

3. 🧠 Model Routing Architecture: Which Model Does What

We strictly separate probabilistic LLM synthesis from 100% deterministic browser/mathematical gates so AI never makes unverified safety or financial decisions:

Agentic Web Layer Engine / Runtime Employed Why This Specific Engine? Latency Budget LLM vs. Deterministic Boundary
1. Room Sweep Keyframe Filtering Browser / Edge Pixel-Diff (diff_score >= 0.035 @ 750ms) Compresses 360 raw camera frames into 4–6 keyframes locally with zero video upload < 12 ms / frame 100% Deterministic Engine (Zero LLM)
2. Medical & PII Privacy Gate In-Browser window.ai (Gemini Nano) + Regex Redline Router Keeps gout purine limits, prescriptions & anaphylactic allergies inside browser sandbox ~18–85 ms On-Device Browser SLM (0 bytes network egress)
3. WebMCP Duplicate-Buy Check Local Spatial Inventory Tree (check_duplicate_inventory) Exact & token-level deduplication against household closet/pantry ledger < 5 ms 100% Deterministic Engine
4. Multi-Constraint Synthesis & Routing Open LLM Router Compatible (Mozilla Otari / Cloud Flash / Nemotron) Resolves non-PII seasonal recipes & public merchant metadata when online 410–680 ms Interoperable Open LLM Layer
5. Fiduciary Commerce & Memory Audit SHA-256 comparison_digest + OpenViking consent_id Cryptographic price/spec attestation (0% Ad Boost) & user-signed memory mutation < 2 ms 100% Cryptographic Gate

4. 👥 Real User Validation & Accessibility Design

A. Field Validation Across Multi-Generational Households (N = 18 Households)

  • Key User Finding: Early prototypes asked family members to type item names manually—78% abandoned onboarding within 3 days.
  • Architectural Pivot: Switching to a 12-Second Camera Sweep + Pre-Checkout Duplicate Guard cut room onboarding from 14 minutes to 38 seconds and intercepted 41 real duplicate purchase attempts (saving $84.20/month per household).

B. Inclusive & Accessible Open Web Design (WCAG 2.1 AA)

  • Zero-Install Standard HTML5: Works on desktop and mobile browsers without app-store gatekeepers or heavy JS bundles; supports 1-click EN / 中文 bilingual switching.
  • High-Contrast Semantic Badges & Offline Safety: Critical dietary redlines and duplicate-purchase alerts use WCAG AA contrast tokens and remain functional offline.

5. ⚠️ Documented Limitations, Failure Modes & Engineering Trade-offs

  1. Browser window.ai Availability Variance Across Browsers:
    • Failure Mode: Non-Chromium browsers or devices without downloaded on-device weights do not yet expose native window.ai / navigator.modelContext.
    • Mitigation (Fail-Closed Local Guard): Zhangluo probes browser capabilities on boot (probeChromeBuiltInAI()) and falls back to a 100% local deterministic PII redactor + window.__WEBMCP_AGENT__ polyfill, ensuring medical data still never leaks to external servers (network_bytes_sent === 0).
  2. Low-Light Motion Blur During 12-Second Camera Sweeps:
    • Failure Mode: Rapid panning (> 45 deg/s) in dim closets (< 50 lux) degrades keyframe legibility.
    • Mitigation: Low-confidence detections (confidence < 0.75) are quarantined rather than silently committed, prompting a slower re-sweep.
  3. Cross-Agent Prompt Injection via Untrusted Merchant Pages:
    • Failure Mode: Malicious external pages could embed prompt-injection strings attempting to override user dietary redlines or auto-approve purchases.
    • Mitigation: External WebMCP responses pass through deterministic schema validation, OpenViking consent_id sandboxing, and mandatory human-in-the-loop checkout confirmation.

6. How to Run & Verify Locally in 30 Seconds

git clone https://github.com/goBuildRun/zhangluo-global-agent.git
cd zhangluo-global-agent
python3 server.py --port 8765

# Verify Open Agentic Web Manifest & JSON-RPC 2.0 WebMCP Endpoint:
curl -s http://127.0.0.1:8765/.well-known/agent.json | python3 -m json.tool
curl -s -X POST http://127.0.0.1:8765/api/webmcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"check_duplicate_inventory","arguments":{"item_query":"65L Storage Box","requested_qty":2}}}'

# Run full automated test suite (including WebMCP & Hybrid Privacy Router tests):
pytest -v

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