Agent skill
glance-test
Run E2E browser tests on any web application using Glance MCP. Use when the user says "test this page," "check this URL," "run E2E tests," "browser test," "test the login flow," "check if the site works," "visual regression," or "screenshot this page." Also use for post-deploy verification and smoke tests.
Install this agent skill to your Project
npx add-skill https://github.com/DebugBase/glance/tree/main/skills/glance-test
Metadata
Additional technical details for this skill
- version
- 1.0.0
SKILL.md
Glance E2E Browser Test
You run end-to-end browser tests using Glance MCP tools. You have a real Chromium browser at your disposal.
Prerequisites
Glance MCP must be configured. If mcp__browser__browser_navigate is not available, tell the user:
claude mcp add glance -- npx glance-mcp
Workflow
1. Get the target
Ask for the URL if not provided. Accept:
- Full URL:
https://example.com - Local:
localhost:3000 - Relative paths (prepend the known base URL)
2. Start session and navigate
mcp__browser__session_start — name: "e2e-{domain}"
mcp__browser__browser_navigate — url
3. Initial assessment
mcp__browser__browser_screenshot — see the page
mcp__browser__browser_snapshot — get DOM structure
mcp__browser__browser_console_messages — check for JS errors
4. Smart page discovery
From the snapshot, identify:
- Navigation links (sidebar, header, footer)
- Forms (login, register, contact, search)
- CTAs (buttons, links)
- Interactive elements (dropdowns, modals, tabs)
5. Test each page
For every discoverable page, run:
navigate → screenshot → assert key elements → check console → check network
Use test_scenario_run for multi-step flows:
{
"name": "Page: /login",
"steps": [
{"name": "Navigate", "action": "navigate", "url": "URL"},
{"name": "Page loaded", "action": "assert", "type": "exists", "selector": "h1"},
{"name": "Screenshot", "action": "screenshot", "screenshotName": "page-name"},
{"name": "No console errors", "action": "assert", "type": "consoleNoErrors"}
]
}
6. Test forms and auth
If login/register forms exist:
- Test with invalid data (expect error message)
- Test with valid data if credentials provided
- Verify redirects and session persistence
7. Generate report
Output a markdown table:
| Page | Steps | Pass | Fail | Issues |
|------|-------|------|------|--------|
| / | 5 | 5 | 0 | None |
| /login | 8 | 7 | 1 | Console error: ... |
Include:
- Total pages tested
- Total steps: X pass, Y fail
- Screenshots of failures
- Console errors found
- Network failures
- Bugs discovered with severity
8. End session
mcp__browser__session_end
Assertion Quick Reference
| Type | Use for |
|---|---|
exists |
Element present |
notExists |
Element absent |
textContains |
Partial text match |
textEquals |
Exact text |
urlContains |
URL check after navigation |
isVisible |
Visibility check |
isEnabled |
Button/input enabled |
consoleNoErrors |
Zero JS errors |
Tips
browser_clickaccepts plain text:"Sign in","Submit","Next"- Always screenshot before and after form submissions
- Check
browser_network_requestsafter login to verify API calls - Use
visual_baseline+visual_comparefor regression testing - Set
BROWSER_HEADLESS=falsefor the user to watch live
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
verl-rl-training
Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.
openrlhf-training
High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.
gguf-quantization
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
Claude Code Guide
Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.
qdrant-vector-search
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
behavioral-modes
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
Didn't find tool you were looking for?