Self-improving browser automation via the auto-research loop. Iteratively runs a browsing task, reads the trace, and improves the navigation skill (strategy.md) until it reliably passes. Supports parallel runs across multiple tasks using sub-agents. Use when you want to build or improve browser automation skills for specific website tasks.
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SKILL.md
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name
autobrowse
description
Self-improving browser automation via the auto-research loop. Iteratively runs a browsing task, reads the trace, and improves the navigation skill (strategy.md) until it reliably passes. Supports parallel runs across multiple tasks using sub-agents. Use when you want to build or improve browser automation skills for specific website tasks.
license
MIT
compatibility
Requires Node.js 18+, browse CLI, and ANTHROPIC_API_KEY. Run from the autobrowse app directory.
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 ${CLAUDE_SKILL_DIR}/references/example-task.md, fill in the URL/goal based on what the user said, and proceed. Tell the user the chosen name in one line.
How to run
Step 1 — Parse arguments and orient
Check what was passed:
--task <name> → single task mode
--tasks a,b,c or --all → multi-task mode (spawn sub-agents)
--iterations N → how many evaluate → improve cycles (default: 5)
--env local|remote → browser environment (default: local; use remote for bot-protected sites)
--browser-trace → opt in to the browser-trace integration (default off). Implies --env remote. If --env local --browser-trace are both passed explicitly, error with: browser-trace requires Browserbase; drop --env local or drop --browser-trace.
If the user passed free-form text instead, map it to one of the above before continuing.
Step 2 — Set up the workspace
All training artifacts (task definitions, strategy iterations, traces, reports) live in a workspace directory in the current working directory — NOT inside ~/.claude/skills/. This keeps the inner agent's file writes out of Claude's home dir and away from permission friction.
If the task directory (./autobrowse/tasks/<task>/task.md) doesn't exist yet, scaffold it:
mkdir -p ./autobrowse/tasks/<task>
cp${CLAUDE_SKILL_DIR}/references/example-task.md ./autobrowse/tasks/<task>/task.md
# Then edit task.md to describe the URL, inputs, steps, and expected JSON output
The skill source at ${CLAUDE_SKILL_DIR} stays read-only — only ./autobrowse/ in CWD gets written to during training. Graduation (final step) writes a single file to ~/.claude/skills/<task>/SKILL.md.
List available tasks:
ls ./autobrowse/tasks/
Step 3 — Multi-task: spawn parallel sub-agents
If running multiple tasks, use the Agent tool to spawn one sub-agent per task simultaneously. Each sub-agent receives a self-contained prompt to run the full autobrowse loop for its task:
"You are running the autobrowse skill for task <name>. Workspace: <absolute-path-to-workspace> (e.g. /path/to/project/autobrowse). Run <N> iterations of: evaluate → read trace → improve strategy.md → repeat. Use --env <env>. Pass --workspace <workspace> to every evaluate.mjs invocation. If the parent invocation used --browser-trace, you MUST use the traced-path block of the SKILL.md loop for every iteration (pre-create session, attach bb-capture, pass --connect-url to evaluate.mjs, stop+bisect, release) — do not fall back to the default single-command path. Follow the autobrowse loop instructions exactly.
When graduating, install the skill to ~/.claude/skills/<task-name>/SKILL.md with proper agentskills frontmatter (name + description). Do not just copy strategy.md — write a self-contained skill.
At the end, output a structured summary with: task name, pass/fail on final run, total cumulative cost, iterations completed, per-iteration table (iter number, turns, cost, status, hypothesis tested), and 2-3 bullet key learnings."
Spawn all sub-agents in parallel, wait for all to complete, then collect their summaries and write the session report.
For single task, skip this step and run the loop directly below.
The Loop (run this for each task)
Iteration start
Check that ./autobrowse/tasks/<task>/task.md exists (scaffold it from the template if not — see Step 2). strategy.md is auto-created empty by the harness on first run.
Requirements
ANTHROPIC_API_KEY must be in the environment (or in a .env file in CWD — evaluate.mjs auto-loads it). If missing, the harness prints a clear error and exits; don't hunt for keys in other paths.
Run the inner agent
Default path (no --browser-trace) — single command, no orchestration:
node ${CLAUDE_SKILL_DIR}/scripts/evaluate.mjs --task <task-name> --workspace ./autobrowse
# or for bot-protected sites:
node ${CLAUDE_SKILL_DIR}/scripts/evaluate.mjs --task <task-name> --workspace ./autobrowse --env remote
This runs the browser session and writes a full trace to ./autobrowse/traces/<task>/latest/.
Traced path (--browser-trace, remote only) — the outer harness pre-creates a Browserbase session, attaches bb-capture as a passive observer, and passes the session's connectUrl to evaluate.mjs so every inner browse call uses --cdp $connectUrl --session autobrowse-main (the canonical browser-trace pattern that gives observers full Network/Console events). Run this block once per iteration with $N set to the 1-indexed iteration number:
# Preflight — fail fast if browser-trace isn't installed alongside autobrowse.
BT_DIR="${CLAUDE_SKILL_DIR}/../browser-trace"if [ ! -f "$BT_DIR/scripts/bb-capture.mjs" ]; thenecho"ERROR: --browser-trace requires the browser-trace skill at $BT_DIR." >&2
echo"Install it by cloning github.com/browserbase/skills and copying skills/browser-trace/" >&2
echo"into the same parent directory as autobrowse (e.g. ~/.claude/skills/browser-trace/)." >&2
exit 1
fi# a. SESSION SETUP — pre-create the keep-alive session and derive its connectUrl
sid=$(browse cloud sessions create --keep-alive --verified --proxies \
| node -e "let s='';process.stdin.on('data',c=>s+=c).on('end',()=>process.stdout.write(JSON.parse(s).id))")
connect_url=$(browse cloud sessions get "$sid" \
| node -e "let s='';process.stdin.on('data',c=>s+=c).on('end',()=>process.stdout.write(JSON.parse(s).connectUrl))")
RUN_ID="run-$(printf '%03d' "$N")"
TRACE_ROOT="./autobrowse/traces/<task-name>/$RUN_ID"mkdir -p "$TRACE_ROOT"export O11Y_ROOT="$TRACE_ROOT/.o11y"# park browser-trace output inside the autobrowse run direxport O11Y_RUN_ID="$RUN_ID"# tells the browse CLI which run dir to write descriptors.ndjson into# b. ATTACH BROWSER-TRACE — passive observer; runs in background
node ${CLAUDE_SKILL_DIR}/../browser-trace/scripts/bb-capture.mjs "$sid""$RUN_ID" &
sleep 2
# c. RUN AUTOBROWSE — connectUrl flag tells evaluate.mjs to inject --cdp/--session# into every inner browse call. The inner agent never sees --remote.
node ${CLAUDE_SKILL_DIR}/scripts/evaluate.mjs \
--task <task-name> --workspace ./autobrowse --env remote \
--connect-url "$connect_url" --run-number "$N"# d. STOP + BISECT + UNIFY — order matters; bisect needs the session to still# exist, and unify-trace joins the bisect output with autobrowse's trace.json# into a single time-ordered NDJSON the outer agent reads first each iter.
node ${CLAUDE_SKILL_DIR}/../browser-trace/scripts/stop-capture.mjs "$RUN_ID"
node ${CLAUDE_SKILL_DIR}/../browser-trace/scripts/bisect-cdp.mjs "$RUN_ID"
node ${CLAUDE_SKILL_DIR}/scripts/unify-trace.mjs \
--trace-dir "$TRACE_ROOT" \
--o11y-dir "$O11Y_ROOT/$RUN_ID"# e. RELEASE
browse cloud sessions update "$sid" --status REQUEST_RELEASE
This writes the inner-agent trace to ./autobrowse/traces/<task-name>/latest/ and the CDP bisect to ./autobrowse/traces/<task-name>/latest/.o11y/<run-id>/. The traced browse CLI also emits per-command rich node descriptors to .o11y/<run-id>/cdp/descriptors.ndjson (one JSON object per page-driving call: target tag/id/role/accessibleName/attributes/xpath/bounding-rect). The descriptors file feeds downstream codegen; it is not required for hypothesis formation — skip it when reading the trace.
The summary has duration, cost, turns, the decision log, and the final JSON output.
If the agent failed or got stuck, look deeper:
Read ./autobrowse/traces/<task-name>/latest/trace.json — search for the failure turn
Read screenshots around the failure point with the Read tool
When --browser-trace was used — start with unified-events.jsonl. The harness joins the agent's turn log and the browser's CDP firehose into one time-ordered NDJSON stream at the run root. One file, source-tagged (source: "agent" | "browser"), interleaved by wall-clock timestamp. Skim it top-to-bottom; the failure cause is usually one or two adjacent lines (the agent issued command X, the browser responded with Y).
The structured files (trace.json, .o11y/<run-id>/cdp/*) are also agent-consumable as drill-downs when the unified stream points at something you need more of:
Need
Drill-down file or command
Per-page totals + timing (events, network counts, errors by page)
.o11y/<run-id>/cdp/summary.json
All failed network requests in one place
.o11y/<run-id>/cdp/network/failed.jsonl
Full console exception payloads (stacktraces, etc.)
.o11y/<run-id>/cdp/console/exceptions.jsonl
Per-page slice (only events on page N)
.o11y/<run-id>/cdp/pages/<pid>/
Full reasoning text / untruncated tool outputs for a specific turn
trace.json (filter by turn === N)
Ad-hoc grouped query (e.g. top hosts, errors-by-page)
The unified stream is the default; drill into structured files only when you need a grouped query, a full-text payload, or filtering the stream can't give you.
Form one hypothesis
Find the exact turn where things went wrong. What single heuristic would have prevented it?
Under --browser-trace, the hypothesis must cite a specific event from unified-events.jsonl (line number or timestamp) — or name the drill-down file if you had to descend into one. This keeps updates evidence-grounded rather than vibes-driven. A hypothesis based only on the agent's commands might say "the click didn't work"; grounded in the unified stream, it can say "line 47 of unified-events.jsonl: browse open was followed by Network.responseReceived status 403 on /api/checkout — switch to --verified --proxies."
Examples:
"After clicking the dropdown, wait 1s — options animate in before they're clickable"
"Navigate directly to /pay-invoice/ — skip the landing page entirely"
"Use browse fill #field_3 value not browse type — this field clears on focus"
"The page shows a spinner at turn 8 — add browse wait timeout 2000 before snapshot"
(with --browser-trace) "At line 47 of unified-events.jsonl, 3 consecutive Network.responseReceived events on /api/availability returned 403 right after browse open — the site is fingerprinting; the next iter needs --verified --proxies."
Update strategy.md
Edit ./autobrowse/tasks/<task-name>/strategy.md. Keep everything that worked. Fix the specific failure. Add a concrete heuristic.
Good strategies have:
Fast path: direct URL or shortcuts to skip exploration
Step-by-step workflow: exact sequence with timing notes
Site-specific knowledge: selector IDs, form field names, success indicators
Failure recovery: what to do when X goes wrong
Judge the result
Read the new summary. Did it pass? Make clear progress?
Pass or progress → keep, next iteration
No progress or regression → revert strategy.md to the previous version and try a different hypothesis
Generate a runnable script (optional)
Once the task has converged, you can produce a deterministic, runnable script
in one or more frameworks via scripts/codegen.mjs. This is one shot of an
LLM call per framework, cached by content hash, with optional verify-against-
fresh-session and rewrite-on-failure.
Each framework gets its own subdirectory under tasks/<name>/<framework>/
with the emitted script and a self-contained scaffold (package.json,
tsconfig.json). The directory is runnable standalone with
cd tasks/<name>/playwright && npm install && npx tsx <name>.ts — the only
runtime requirement is BROWSERBASE_API_KEY (plus ANTHROPIC_API_KEY for
the Stagehand target).
Builtin frameworks: playwright, stagehand. Add a custom framework with
--prompt-template <path> --frameworks custom (and provide your own runner
or pass --no-verify).
Common flags:
Flag
Purpose
--frameworks a,b,...
Comma-separated; default playwright
--verify / --no-verify
Run the produced script against a fresh BB session; default --verify
--max-retries N
Rewrite-on-verify-failure cap; default 2
--cache-only
Error if cache miss (CI-friendly)
--force
Bust the cache
--dry-run
Estimate prompt size + cost; don't call the LLM
--run <id>
Force a specific run-NNN (default: latest passing)
Output is one JSON line per framework on stdout. Non-zero exit if any
selected framework's final state is passed: false.
See references/playwright-cdp-bridge.md for the canonical
connectOverCDP patterns the emitted scripts follow.
After all iterations — publish if ready
If the task passed on 2+ of the last 3 iterations or has reached the max iteration limit, install it as a Claude Code skill. Do not just copy strategy.md — the skill must be self-contained and useful to someone who has never seen this codebase. If graduating at max iterations without a clean pass, note the known failure point but still document everything learned.
Install by writing to ~/.claude/skills/<task-name>/SKILL.md:
mkdir -p ~/.claude/skills/<task-name>
Use this structure for the SKILL.md:
---
name: <task-name>description: <1-2 sentences describing what this skill does and when to use it. Include trigger keywords.>
---# <TaskTitle> — Browser Skill## Purpose
<1-2 sentences: what this automates and why it exists.>
## When to Use<Whenshouldsomeonereachforthisskill.>## Browse CLI Reference
The inner agent uses the `browse` CLI. Key commands for this task:
-`browse stop` — kill existing session (always run before switching to remote)
-`browse open <url> --remote` — start a fresh Browserbase cloud session and navigate
-`browse open <url> --local` — start a clean local browser and navigate
-`browse tab new <url>` — open URL in a new tab
-`browse wait load` — wait for page to finish loading
-`browse wait timeout <ms>` — wait a fixed amount of time for spinners or animations
-`browse wait selector "<selector>"` — wait for an element to become visible
-`browse get title` — verify you're on the right page
-`browse get text body` — extract all visible text (preferred for content extraction)
-`browse snapshot` — get accessibility tree; each node has a ref in `[X-Y]` format (e.g. `[0-5]`, `[2-147]`)
-`browse click [X-Y]` — click element by ref from the latest snapshot (include the brackets)
**Never use `--session <name>` flags in SKILL.md.** Named sessions are a parallel-run workaround — they contaminate skills with infrastructure concerns. Skills must work in isolation with the default session.
## Workflow### Step 1 — Start session<exactbrowsecommandsinorder>### Step 2 — Navigate<exactURLandverificationsteps>### Step 3 — Extract<exactextractioncommands>### Step 4 — Output<whatJSONtoemit, referencingtheschemabelow>## Site-Specific Gotchas<Bulletlistofeveryhard-wonheuristicfromtheiterations.Thisisthecorevalueoftheskill.>## Failure Recovery<Whattodowhennavigationfails, sessioniscontaminated, orextractionreturnsgarbage>## Expected Output```json
<paste the exact expected output schema from task.md>
After writing the SKILL.md, confirm it's installed:
```bash
ls ~/.claude/skills/<task-name>/SKILL.md
The skill is now available as /<task-name> in Claude Code.
Final report (multi-task mode)
After all sub-agents complete, print a markdown table:
Task
Iterations
Final Status
Graduated
Cost
google-flights
5
✅ pass
yes
$0.42
amazon-add-to-cart
5
❌ fail
no
$1.20
Then write a persistent session report to ./autobrowse/reports/ so there's a durable record of the run inside the workspace:
mkdir -p ./autobrowse/reports
Write the file ./autobrowse/reports/YYYY-MM-DD-HH-MM-<tasks>.md with:
Only edit strategy.md — never touch task.md (unless creating it from the template) or evaluate.mjs
Stay in the workspace — all training writes go to ./autobrowse/, never to ~/.claude/skills/autobrowse/. The skill source is read-only.
One hypothesis per iteration — test one change at a time
Build on wins — keep what worked, add to it
Trust the trace — the inner agent shows exactly what it saw and did
Graduate to ~/.claude/skills/ — the only file you write there is the final graduated SKILL.md
Don't release before bisecting — under --browser-trace, the order at the end of each iteration is non-negotiable: stop-capture → bisect-cdp → browse cloud sessions update REQUEST_RELEASE. Bisect depends on the session still existing when the trace stops.
