AutoBrowse, Self-Improving Browser Skill

Build reliable browser automation skills through iterative experimentation. An inner agent browses the site (evaluate.ts). You, the outer agent, read what happened and improve the instructions (strategy.md). Repeat until it passes consistently.

Entry Points

Invocation is flexible, both explicit flags and free-form natural language work:

/autobrowse --task google-flights
/autobrowse --task google-flights --iterations 10 --env remote
/autobrowse --task google-flights --browser-trace
/autobrowse --tasks google-flights,amazon-add-to-cart
/autobrowse --all

# Also fine, parse freely:
/autobrowse https://flights.google.com/
/autobrowse book a flight on delta.com
/autobrowse fix the existing google-flights skill

--browser-trace (default off, remote-only): pairs each iteration with the sibling browser-trace skill, wraps the inner agent in a CDP capture for per-page network/console/page-lifecycle evidence. Implies --env remote; errors if combined with --env local. Requires the sibling browser-trace skill present at ${CLAUDE_SKILL_DIR}/../browser-trace/, and the BROWSERBASE_API_KEY env var.

When the user drops a URL or free-form instruction instead of --task <name>:

• If an existing task in ${WORKSPACE}/tasks/ clearly matches the site/intent, use it.
• Otherwise, pick a short kebab-case name, create ${WORKSPACE}/tasks/<name>/task.md from ${CLAUDE_SKILL_DIR}/references/example-task.md, fill in the URL/goal based on what the user said, and proceed. Tell the user the chosen name in one line.

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How to run

Step 1, Parse arguments and orient