browser-fetch

Delegate browser automation to a cost-effective subagent, preserving the main agent's context window.

Why This Skill?

• Problem:

  agent-browser snapshot

  can consume 10,000+ tokens on complex pages
• Solution: Haiku subagent processes snapshots and returns only summaries (~100 tokens)
• Result: 90%+ context reduction while maintaining full browser capabilities

Prerequisites

Install agent-browser

npm install -g agent-browser
agent-browser install

Install clipper

npm install -g @philschmid/clipper

Uses Mozilla Readability + Turndown internally — same stack as Obsidian Web Clipper.

Windows Workaround

On Windows (Git Bash), the daemon may not auto-start. Run manually:

node "$(npm root -g)/agent-browser/dist/daemon.js" &
sleep 3

Basic Flow

Main Agent                        Haiku Subagent
    │                                   │
    │  Task: "Open URL, summarize"      │
    ├──────────────────────────────────►│
    │                                   │  1. agent-browser open
    │                                   │  2. snapshot → save to file
    │                                   │  3. build summary
    │   "Page summary + key refs"       │
    │◄──────────────────────────────────┤
    │                                   │
    │  Task: "Click @e5, summarize"     │
    ├──────────────────────────────────►│
    │                                  ...

Snapshot Options

-i

-i -c

-i -d 2

-i -s "main"

Summary Format (Critical)

Subagent must return structured summaries, not raw element lists.

Good Example

Product listing page (127 items displayed)

Structure:
- Filters: category (@e12), price range (@e18), search (@e24)
- Sort: date (@e30), popularity (@e31)

Sample items:
- "Product A" $29.99 (@e45)
- "Product B" $49.99 (@e52)
- "Product C" $19.99 (@e58)

Ready for instructions.
(debug: 001.txt)

Bad Example

- @e1 Logo
- @e2 Login button
- @e3 Menu
- @e4 Search
- @e5 Footer

→ No context. Main agent cannot make informed decisions.

Invocation Template

Opening a Page

Task(
  model: haiku,
  subagent_type: general-purpose,
  prompt: """
  Use agent-browser to open {URL}.

  Steps:
  1. agent-browser open {URL}
  2. agent-browser snapshot -i -c > scratchpad/browser-session/001.txt
  3. Append to index.log: 001 | {time} | {URL} | {summary}

  Return ONLY a structured summary:
  - Page type and overview (e.g., "Login page", "Product list with 50 items")
  - Key interactive elements with @refs
  - Do NOT include raw snapshot data

  Format:
  {Page description}

  Structure:
  - {feature}: {description} (@ref)

  Key elements:
  - {element description} (@ref)

  Ready for instructions.
  (debug: 001.txt)
  """
)

Performing Actions

Task(
  model: haiku,
  subagent_type: general-purpose,
  prompt: """
  Use agent-browser:
  1. agent-browser fill @e1 "value"
  2. agent-browser click @e3
  3. agent-browser snapshot -i -c > scratchpad/browser-session/002.txt
  4. Update index.log

  Return structured summary only.
  """
)

Complex Pages

If snapshot exceeds limits, use additional constraints:

agent-browser snapshot -i -c -d 2 > file.txt   # Depth limit
agent-browser snapshot -i -c -s "#content"     # Scope to selector

Rules

Main Agent

• Trust subagent summaries
• Do NOT read raw files (scratchpad/browser-session/*.txt) unless debugging
• Raw data is for troubleshooting only

Subagent

• Always save snapshots to files (never return raw data)
• Append to index.log for history
• Use

  --session

  flag to maintain browser state
• Return concise, structured summaries

File Structure

scratchpad/browser-session/
├── index.log    # History (debug reference only)
├── 001.txt      # Raw snapshot data
├── 002.txt
└── ...

index.log Format

# browser-session index (debug only - do not read unless troubleshooting)

001 | 14:23:45 | https://example.com/login     | Login form
002 | 14:24:12 | https://example.com/dashboard | Dashboard with 5 widgets

Ending Session

Task(
  model: haiku,
  subagent_type: general-purpose,
  prompt: "Run: agent-browser close"
)

Web Clip (HTML → Markdown)

Convert web pages to clean Markdown using

clipper

Basic Usage

clipper clip -u "https://example.com/article" -o scratchpad/browser-session/clip.md

This is the preferred method. Quality is equivalent to Obsidian Web Clipper (same Readability + Turndown stack).

Output Formats

-f md

-f json

Batch Clipping

clipper crawl -u "https://docs.example.com" -g "https://docs.example.com/**/*" -o dataset.jsonl

When to Use What

clipper clip -u