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Skillsautobrowse-cc

autobrowse-cc

Coding & development

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Updated 10-15 17:25

About this skill

autobrowse-cc

Self-improving browser automation, key-free. Port of Browserbase's autobrowse: the inner agent is claude -p (reuses your session/Bedrock auth — no ANTHROPIC_API_KEY) and the browser primitive is the local chrome-cdp skill (no browse CLI, no Browserbase). The claude -p --output-format stream-json transcript serves as the trace.

You (the main session) ARE the outer loop. Drive it by hand per the algorithm below — this is not a bash for-loop; you read each trace and reason about the next change.

Layout

./autobrowse-cc/                 # runtime workspace, in CWD (created on demand)
├── tasks/<task>/task.md         # input spec (you author from references/example-task.md)
├── tasks/<task>/strategy.md     # accumulated heuristics (starts empty, you edit each iter)
└── traces/<task>/run-NNN.jsonl  # stream-json transcript per run; latest.jsonl symlinks it

Browser driving and graduation reuse the sibling skills. Prereqs: Node 22+ (chrome-cdp), jq, and a working claude CLI. Default browser is the isolated Chrome profile (~/.chrome-debug-profile) — the loop never touches the user's real browser.

Algorithm

1. Set up the task

  • If ./autobrowse-cc/tasks/<task>/task.md doesn't exist, create it from references/example-task.md. Pin down the success condition precisely — the loop is only as good as what "done" means. Ask the user for URL, inputs, and steps if unclear.
  • Leave strategy.md empty on first run (the runner creates it).

2. Iterate (default max 5)

Repeat until the stop condition in step 3:

  1. Run one attempt: 
    scripts/run-iteration.sh <task>
    It launches isolated Chrome, runs the claude -p inner agent scoped to cdp.mjs, writes traces/<task>/run-NNN.jsonl, and prints the verdict JSON + trace path.
  2. Read the trace. Open traces/<task>/latest.jsonl. Walk the assistant turns and tool calls; find the EXACT turn where it failed or stalled (wrong selector, missing wait, unexpected page state, bad assumption). Quote it.
  3. Form ONE hypothesis — a single concrete heuristic that would prevent that specific failure (e.g. "wait for #results to appear before clicking", "use selector [name=q] not the placeholder"). One change per iteration; never batch fixes.
  4. Edit strategy.md — append the heuristic under the right section (Fast Path / Workflow / Site-Specific Knowledge / Failure Recovery). Keep everything that worked.
  5. Judge. Re-run (back to step 1). If the verdict improved (passed, or got measurably further), keep the strategy edit. If it regressed, revert that edit and try a different hypothesis. Log nothing else — the traces and strategy.md are the record.

3. Stop condition

Stop when the task passes on 2 of the last 3 runs, or you hit max iterations. If max is reached without 2/3 passing, report the best run and the open failure — don't publish a flaky skill.

4. Graduate

On success, synthesize a self-contained skill at ~/.claude/skills/<task>/SKILL.md using references/example-published-skill.md as the template. Fold the winning strategy.md and the verified step sequence into it — do not raw-copy strategy.md; the published skill must reproduce the task from itself alone. Then tell the user the path and the pass rate.

Scope (deliberately dropped vs upstream autobrowse)

No Browserbase/remote sessions, no Playwright/Stagehand codegen, no parallel multi-task fan-out. Single local task against isolated Chrome. Add those back only if a task needs bot-protection handling or multi-task throughput.