cbrowser

v18.68.0

Published

19 days ago

Cognitive browser automation that thinks like your users—and helps AI agents navigate too. Simulate real user cognition with abandonment detection, constitutional safety, chaos engineering, and UX friction discovery. Sites that pass CBrowser's cognitive t

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4,382

CBrowser — Cognitive Browser Automation

The browser automation that thinks like your users. 120 MCP tools. 26 cognitive traits. 11 disability personas. The only framework that predicts when users give up.

npm install cbrowser
npx cbrowser cognitive-effort --url "https://your-site.com" --persona first-timer

5-Minute Quickstart

Get from zero to your first cognitive insight in 3 commands:

# 1. Install CBrowser
npm install cbrowser

# 2. Install the browser engine (~150MB)
npx playwright install chromium

# 3. Run your first cognitive audit
npx cbrowser cognitive-effort --url "https://your-site.com" --persona first-timer

What you get: A cognitive transport score (0-1), abandonment risk percentage, and the UX bottleneck — in under 30 seconds.

No API key needed for basic commands (navigate, screenshot, click, extract, explore). Cognitive journeys require an Anthropic API key:

npx cbrowser config set-api-key <your-anthropic-key>

Check your environment: Run npx cbrowser doctor to verify everything is set up correctly.

Accessibility: CBrowser supports --no-color (or NO_COLOR env var), --plain (no emoji/decorations), and --json-output (structured JSON) for screen readers, CI pipelines, and scripting.

Cognitive Transport Chain

The 6-layer Sequential Transport Chain computes exactly how hard your page is for any persona — and predicts whether they'll abandon:

| Layer | What It Measures | Research Basis | |-------|-----------------|----------------| | Saliency | Visual attention capture | CIE-Lab W₂ perceptual model | | Cognitive Load | Information processing demand | Sweller (1988) CLT | | Decision | Choice complexity and fatigue | Hick-Hyman Law | | Motor | Physical interaction difficulty | Grossman & Balakrishnan (2005) | | Frustration | Emotional cost accumulation | Ceaparu et al. (2004) | | Readability | Text comprehension effort | Perry & Zorzi (2013) reading model |

npx cbrowser cognitive-effort --url "https://your-site.com" --persona first-timer
# → CTC: 0.76, abandonment risk: 42%, bottleneck: decision

Returns: total CTC score, per-layer breakdown, bottleneck identification, abandonment risk percentage, and motor accessibility overlay.

Visual Overlays & Attention Analysis

See where users look, what they miss, and whether your CTAs capture attention — per persona:

# Full visual cognitive story — 4 annotated images + narrative
npx cbrowser visual-cognitive-story --url "https://your-site.com" --persona cognitive-adhd

# Attention heatmap — where does this persona look?
npx cbrowser attention-analysis --url "https://your-site.com" --persona first-timer

# Compare how two personas experience the same page
npx cbrowser attention-compare --url "https://your-site.com" --persona-a first-timer --persona-b power-user

Overlays generated:

Attention heatmap — CIE-Lab saliency on grayscale base (red = high attention)
Motor accessibility — Green/yellow/red per element by P(hit)
Attention quality — CTAs green, distractors red, headings blue
Comparison diff — Blue = persona A attention, red = persona B

Metrics: CTA capture rate, value prop salience, distractor ratio, quality score (0-100), entropy.

AI Friendliness Suite

Five tools to make your site ready for the AI agent era:

| Tool | What It Does | |------|-------------| | agent_ready_audit | Score site on findability, stability, accessibility, semantics (A-F grade) | | ai_benchmark | Compare AI-friendliness across competitor URLs | | webmcp_ready_audit | Audit MCP server for WebMCP compatibility | | remediation_patches | Generate actionable code fixes for audit findings | | llms_txt_generate | Generate AI-readable llms.txt site description |

npx cbrowser agent-ready-audit "https://your-site.com" --html
npx cbrowser ai-benchmark "https://site-a.com,https://site-b.com"

Cognitive User Simulation

26 research-backed cognitive traits + 10 motivational values model how real users think, struggle, and give up:

| Trait | Research Basis | What It Models | |-------|---------------|----------------| | Patience | Nah (2004); Nielsen (1993) | Tolerance for delays; abandonment at 8+ seconds | | Working Memory | Miller (1956) | 7±2 item capacity; affects form complexity tolerance | | Comprehension | Card, Moran & Newell (1983) | UI convention understanding; GOMS model timing | | Risk Tolerance | Kahneman & Tversky (1979) | Prospect theory; loss aversion affects CTA clicks | | Self-Efficacy | Bandura (1977) | Belief in ability to solve problems; low = faster abandonment | | Satisficing | Simon (1956) | Accept "good enough" vs. optimize; 50% faster decisions | | Trust Calibration | Fogg (2003) | 8 trust signals; affects click-through by 40% | | Information Foraging | Pirolli & Card (1999) | "Scent" following behavior; predicts navigation patterns | | Social Proof | Cialdini (2001) | Influence of reviews, ratings, popularity indicators | | FOMO | Przybylski et al. (2013) | Fear of missing out; urgency and scarcity responses |

See Trait Index for all 26 traits including: Persistence, Resilience, Curiosity, Change Blindness, Anchoring Bias, Time Horizon, Attribution Style, Metacognitive Planning, Procedural Fluency, Transfer Learning, Authority Sensitivity, Emotional Contagion, Mental Model Rigidity, Interrupt Recovery, Reading Tendency, and Site Familiarity.

Full documentation: Research Methodology · Trait Index · Bibliography

17 Built-in Personas

6 general: first-timer, power-user, mobile-user, screen-reader-user, elderly-user, impatient-user

11 accessibility: motor-impairment-tremor, low-vision-magnified, cognitive-adhd, dyslexic-user, deaf-user, elderly-low-vision, color-blind-deuteranopia, autism-spectrum, intellectual-disability, aphasia-receptive, dyscalculia

Values System

Beyond cognitive traits, CBrowser models 10 motivational values from three psychological frameworks:

| Framework | Research Basis | |-----------|---------------| | Schwartz's Universal Values | Schwartz (1992) — 10 core values: Power, Achievement, Hedonism, Stimulation, Self-Direction, Universalism, Benevolence, Tradition, Conformity, Security | | Self-Determination Theory | Deci & Ryan (1985) — Autonomy, Competence, Relatedness | | Maslow's Hierarchy | Maslow (1943) — 5 need levels |

See Values Framework for full documentation.

Custom Persona Builder

# Interactive questionnaire (8 core traits)
npx cbrowser persona-questionnaire start

# Comprehensive questionnaire (all 26 traits)
npx cbrowser persona-questionnaire start --comprehensive --name "my-tester"

# From a description — AI generates trait values
npx cbrowser persona-create "A 68-year-old retiree who just got their first smartphone"

Abandonment Detection

The simulation stops when a realistic user would give up:

⚠️ ABANDONED after 8 steps
Reason: Patience depleted (0.08) - "This is taking too long..."
Friction points:
  1. Password requirements unclear (step 4)
  2. Form validation error not visible (step 6)

Accessibility Empathy Testing

Simulate how users with disabilities experience your site:

npx cbrowser empathy-audit "https://your-site.com" \
  --goal "complete signup" \
  --disabilities "motor-impairment-tremor" \
  --html

Constitutional AI Safety

AI agents need boundaries. CBrowser classifies every action by risk level:

| Zone | Examples | Behavior | |------|----------|----------| | 🟢 Green | Navigate, read, screenshot | Auto-execute | | 🟡 Yellow | Click buttons, fill forms | Log and proceed | | 🔴 Red | Submit, delete, purchase | Requires verification | | ⬛ Black | Bypass auth, inject scripts | Never executes |

Site Knowledge System

CBrowser learns your site over time:

Page Understanding — DOM analysis, page type classification, available affordances
Site Model Learning — Persistent knowledge graph across sessions
Cross-Session Profiles — AES-256-GCM encrypted cookie/state profiles
Goal Decomposition — Sub-goal trees with fallback strategies

Natural Language Testing

# Test: Checkout Flow
go to https://your-site.com/products
click "Add to Cart" button
verify page contains "1 item in cart"
click checkout
fill email with "[email protected]"
click "Place Order"
verify url contains "/confirmation"

npx cbrowser test-suite checkout-test.txt --html

# Auto-repair broken tests
npx cbrowser repair-tests broken-test.txt --auto-apply --verify

Visual Testing

# AI visual regression
npx cbrowser ai-visual capture "https://your-site.com" --name homepage
npx cbrowser ai-visual test "https://staging.your-site.com" homepage --html

# Cross-browser (Chrome, Firefox, Safari)
npx cbrowser cross-browser "https://your-site.com" --html

# Responsive (mobile, tablet, desktop)
npx cbrowser responsive "https://your-site.com" --html

# A/B comparison (staging vs production)
npx cbrowser ab "https://staging.your-site.com" "https://your-site.com" --html

Competitive UX Benchmark

Run identical cognitive journeys across your site and competitors:

npx cbrowser competitive-benchmark \
  --sites "https://your-site.com,https://competitor-a.com,https://competitor-b.com" \
  --goal "sign up for free trial" \
  --persona first-timer \
  --html

Geo Proxy

Test from 12 global regions via residential proxies:

npx cbrowser cognitive-journey \
  --start "https://your-site.com" \
  --persona first-timer \
  --goal "sign up" \
  --geo-region uk

Regions: us-west, us-east, us-central, uk, germany, france, japan, australia, brazil, india, canada, singapore

MCP Server Integration

CBrowser runs as an MCP server for Claude.ai, Claude Desktop, and Claude Code.

Claude.ai (Easiest — No Install)

Add the MCP connector and optionally install the Claude.ai Skill:

Go to Customize → Connectors → "Add custom connector"
Paste: https://demo.cbrowser.ai/mcp
Download the Claude.ai Skill (.zip) — gives Claude context about tools, pricing, and workflows
Go to Customize → Skills → Upload the zip

Note: The Claude.ai Skill is a lightweight knowledge file for the web interface. It is NOT the same as the Claude Code Skill (see below).

Claude Code Skill (CLI — Not for Claude.ai)

For Claude Code terminal users:

curl -fsSL https://raw.githubusercontent.com/alexandriashai/cbrowser/main/scripts/install-skill.sh | bash
npm install -g cbrowser && npx playwright install

The Claude Code Skill is a full CLI integration with workflow routing, TypeScript tools, persistent memory, and constitutional safety. See Skill Installation Guide for details.

Claude Desktop

{
  "mcpServers": {
    "cbrowser": {
      "url": "https://demo.cbrowser.ai/mcp"
    }
  }
}

Local MCP Server

{
  "mcpServers": {
    "cbrowser": {
      "command": "npx",
      "args": ["cbrowser", "mcp-server"]
    }
  }
}

108 MCP Tools

| Category | Tools | Count | |----------|-------|-------| | Navigation | navigate, screenshot, scroll, extract, analyze_page, find_element_by_intent | 6 | | Interaction | click, smart_click, fill, dismiss_overlay | 4 | | Cognitive Core | cognitive_journey_init, cognitive_journey_update_state, cognitive_journey_autonomous, cognitive_effort, cognitive_load_estimate, site_cognitive_assessment | 6 | | Cognitive Transport | cognitive_distance, cognitive_interpolate, cognitive_coverage, transport_map | 4 | | Attention & Visual Story | attention_analysis, attention_compare, visual_cognitive_story | 3 | | Persona | list_cognitive_personas, compare_personas, persona_create_*, persona_questionnaire_*, persona_trait_lookup, persona_values_* | 15 | | Testing | nl_test_inline, nl_test_file, generate_tests, repair_test, detect_flaky_tests, coverage_map | 6 | | Visual Testing | visual_baseline, visual_regression, responsive_test, cross_browser_test, cross_browser_diff, ab_comparison | 6 | | Site Intelligence | page_understand, site_model_query, site_model_status, site_profile_* | 6 | | AI Friendliness | agent_ready_audit, ai_benchmark, webmcp_ready_audit, remediation_patches, llms_txt_generate, llms_txt_validate, llms_txt_diff, structured_data_suggest | 8 | | Analysis | hunt_bugs, chaos_test, competitive_benchmark, empathy_audit | 4 | | Performance | perf_baseline, perf_regression | 2 | | Marketing (Enterprise) | marketing_campaign_*, marketing_audience_discover, marketing_compete, marketing_funnel_analyze, marketing_influence_matrix, marketing_lever_analysis, marketing_personas_list, list_influence_patterns | 11 | | Security | security_audit, web_security_scan | 2 | | Stealth (Enterprise) | stealth_enable, stealth_disable, stealth_status, stealth_check, stealth_diagnose, cloudflare_detect, cloudflare_wait | 7 | | Session & Browser | save_session, load_session, delete_session, list_sessions, list_baselines, browser_health, browser_recover, reset_browser, heal_stats, status | 10 | | Utility | assert, ask_user, set_api_key, api_key_status, clear_api_key, get_api_key_prompt | 6 |

Token Cost & Selective Loading

120 MCP tools consume ~45,000 tokens in LLM context. For cost-sensitive use, load selectively:

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import {
  registerNavigationTools,
  registerInteractionTools,
  registerExtractionTools,
} from "cbrowser/mcp-tools";

const server = new McpServer({ name: "my-app", version: "1.0.0" });
const context = { getBrowser: () => browser };

// ~5,000 tokens instead of ~45,000
registerNavigationTools(server, context);
registerInteractionTools(server, context);
registerExtractionTools(server, context);

Categories: navigation, interaction, extraction, assertion, analysis, session, healing, visualTesting, testing, bugAnalysis, personaComparison, cognitive, cognitiveTransport, attention, siteKnowledge, values, performance, audit, browserManagement, security, marketing, remediation, llmsTxt.

CI/CD Integration

GitHub Actions

name: CBrowser Tests
on: [pull_request]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: alexandriashai/cbrowser@v18
        with:
          test-file: tests/e2e/checkout.txt
          sensitivity: strict

Docker

docker run --rm -v $(pwd)/tests:/work/tests ghcr.io/alexandriashai/cbrowser:latest \
  test-suite tests/checkout.txt --html

API Reference

import { CBrowser } from 'cbrowser';

const browser = new CBrowser({
  headless: true,
  persistent: true,
});

await browser.navigate('https://example.com');

const result = await browser.smartClick('Sign In', {
  maxRetries: 3,
  minConfidence: 0.8,
});

const assertion = await browser.assert("page contains 'Welcome'");
if (!assertion.passed) {
  console.error(assertion.message);
}

await browser.close();

Modular Imports

import { runVisualRegression, runCrossBrowserTest } from 'cbrowser/visual';
import { runNLTestSuite, detectFlakyTests, repairTest } from 'cbrowser/testing';
import { huntBugs, runChaosTest, findElementByIntent } from 'cbrowser/analysis';
import { capturePerformanceBaseline, detectPerformanceRegression } from 'cbrowser/performance';

Configuration

| Variable | Default | Description | |----------|---------|-------------| | CBROWSER_DATA_DIR | ~/.cbrowser | Data storage directory | | CBROWSER_HEADLESS | true | Run headless | | CBROWSER_BROWSER | chromium | Browser engine | | CBROWSER_TIMEOUT | 30000 | Default timeout (ms) | | CBROWSER_PROXY | — | Proxy URL |

npx cbrowser config set-api-key  # Required for cognitive journeys

Enterprise Edition

CBrowser Enterprise adds:

| Feature | Description | |---------|-------------| | Marketing Suite | Test which design/copy/UX patterns influence which buyer segments | | 8 Marketing Personas | B2B (enterprise-buyer, startup-founder, procurement-manager, technical-evaluator) + Consumer (impulse-shopper, price-researcher, loyal-customer, skeptical-first-timer) | | Influence Matrix | Conversion effectiveness for variant × persona combinations | | Lever Analysis | Which psychological persuasion patterns work for each persona | | Constitutional Stealth | Full stealth measures for authorized penetration testing | | Web Security Scan | OWASP-based security scanning |

All 120 MCP tools included with no rate limits.

License

MIT License — Free and open source. See LICENSE.