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browser-jev-automation

Jev-driven browser automation: Jev picks operations, programs execute, a text model writes field values only when Jev cannot pick one from the goal.

Install / Use

npx skills add notque/vexjoy-agent --skill browser-jev-automation

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

89/100

Category

Automation

Supported Platforms

Universal

Our assessment of browser-jev-automation

browser-jev-automation scores 89/100 on our quality scale, 1245th of 2,870 Automation skills we index (top 44%).

Its SKILL.md is 14 KB long, well organised into 18 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.

It has 425 GitHub stars, a meaningful sign that others use it.

Substance
30/30
Structure
18/20
Description
15/15
Adoption
11/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated yesterday, so browser-jev-automation is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

browser-jev-automation compared with similar skills

All 4 of these similar skills score higher than browser-jev-automation; compare them before choosing.

SkillScoreStarsUpdatedFormat
browser-jev-automation (this skill)by notque894251d agoSKILL.md
Agent-Reachby Panniantong10090.5k19d agoCLAUDE.md
headroomby headroomlabs-ai10074.4ktodayCLAUDE.md
Scraplingby D4Vinci10085.6ktodayMCP Server
crawl4aiby unclecode10084.8k9d agoMCP Server

Frequently asked questions

How do I install browser-jev-automation?
Run npx skills add notque/vexjoy-agent --skill browser-jev-automation. The install tabs above show the steps for each supported agent.
Which AI agents does browser-jev-automation work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is browser-jev-automation safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is browser-jev-automation still maintained?
The repository was last updated yesterday, so browser-jev-automation is actively maintained.

name: browser-jev-automation description: "Jev-driven browser automation: Jev picks operations, programs execute, a text model writes field values only when Jev cannot pick one from the goal." version: 1.1.0 context: fork routing: category: infrastructure pairs_with: - testing triggers: - "browser automation" - "browser use" - "web scraping with jev" - "jev browser" - "automated browsing" - "fill form" - "click through" - "navigate site" not_for: "Manual browser testing, Playwright E2E test suites, or screenshot comparison. Use e2e-testing or testing-preferred-patterns for those."

Browser Jev Automation

Zero-dependency browser harness. Programs read the DOM and execute actions, Jev makes every judgment call, an LLM writes text only when the goal does not already contain the value. Built in-house; no pip or npm packages.

Quick start

python3 scripts/jev-browser-agent.py \
  --url http://127.0.0.1:8000/ \
  --goal "Sign in with username alice, choose country Canada, and submit." \
  --check-text-contains "Welcome alice" --json-compact

Requires TYPESAFE_API_KEY, Node 22+, and a local Chromium (Playwright cache or CHROME_PATH). Output is one JSON object: status (done|blocked|budget|error), reason, steps, requests, final_url, verify, log (full probability distributions per step), usage.

Measured on a local login form: 5 steps, 7 Jev calls, 1.4 s wall, zero LLM tokens, goal verified.

Architecture: three tiers applied to browser control

| Tier | Role | Cost | |---|---|---| | Programs (tier 1) | Snapshot DOM, extract goal candidates, execute actions, deterministic checks, secret scrubbing | CPU only | | Jev (tier 2) | Pick operation + target, pick field value from goal candidates, verify goal | ~$0.042/M tokens, <300 ms | | LLM (tier 3) | Compose text for TYPE_TEXT only when Jev says no goal candidate fits | Per-token, rare |

One Jev call per decision cycle. Speculative fan-out: operation Choice + per-operation target Choices evaluated in one forward pass. Only the target matching the selected operation executes.

Components

| File | Role | |---|---| | scripts/lib/jev_browser/snapshot.js | In-page snapshot: viewport-visible controls, labels, values, operations, code-owned node ids, freshness guards | | scripts/lib/jev_browser/cdp_driver.mjs | Node ESM, node: builtins only. Launches Chromium, speaks CDP over the built-in WebSocket, evaluates in an isolated world, serves JSON-lines commands: open, observe, fresh, act, navigate, screenshot, close | | scripts/jev-browser-decide.py | One Jev call: operation + target with speculative fan-out, validated against observed ids | | scripts/jev-browser-verify.py | Independent Jev goal check (goal_met Noul, evidence Score, has_error, page_loaded, evidence_element Choice) plus deterministic url_contains / text_contains checks that veto | | scripts/jev-browser-agent.py | Loop: preflight, observe, scrub, decide, text (secret, Jev pick, LLM), freshness, act, log, verify |

CLI

| Flag | Meaning | |---|---| | --url, --goal | Required. Loopback URLs only unless --allow-remote | | --check-url-contains X, --check-text-contains Y | Deterministic checks that must pass for DONE | | --secret-env LABEL=ENV_VAR | Type the variable's value into fields whose label contains LABEL; unset variable fails preflight | | --allow-host HOST | Permit one host and its subdomains (repeatable). Off-origin navigation elsewhere is reverted | | --allow-remote | Permit any host. Page text then reaches Jev and, for composed text, the text model | | --header NAME=ENV_VAR | Send a header on every request with the variable's value (staging bypass tokens). Never logged | | --trace FILE | Write every observed, scrubbed snapshot to FILE | | --headed | Show the browser window | | --max-steps (60), --max-requests (120) | Budgets; requests count Jev calls including text picks and verifies | | --json-compact | Single-line output |

| Env | Meaning | |---|---| | TYPESAFE_API_KEY | Required | | JEV_KEY_ONLY=1 | Skip the Claude Code plugin toggle check (cron, standalone) | | CHROME_PATH | Chromium binary; default is the newest Playwright cache build | | JEV_BROWSER_SANDBOX=1 | Forbid the --no-sandbox fallback | | TEXT_MODEL (claude-opus-4-6), TEXT_MODEL_BACKEND (auto | api | claude-cli), TEXT_MODEL_BASE_URL (https://api.anthropic.com), TEXT_MODEL_API_KEY (falls back to ANTHROPIC_API_KEY), TEXT_MODEL_REASONING (none) | Tier 3 text model. auto uses the API when a key is set, else claude -p (logged-in CLI, run from /tmp, no tools). Owner prefers opus 4.6 here | | JEV_BROWSER_DEBUG=1 | Enables the driver's debug_eval command for development |

Standalone page checks and audits

jev-browser-verify.py also opens pages itself:

python3 scripts/jev-browser-verify.py --url http://127.0.0.1:8002/five-star \
  --goal "at least 8 promotions can be toggled" --goal "there is a Start button"
python3 scripts/jev-browser-verify.py --audit-file pages.json   # {"base": "...", "pages": {"/path": ["goal", ...]}}

One browser per audit, one snapshot per page, one Jev call per goal (~100-200 ms each). passed needs goal_met and evidence score >= 0.5. Same --allow-host, --header, --check-* flags as the agent.

Safety invariants

  • Model output never becomes selectors, coordinates, or JavaScript. Every action carries an integer node id issued by snapshot.js; the driver resolves geometry itself and rejects covered, hidden, disabled, or read-only targets.
  • The node registry lives in a CDP isolated world. Page scripts cannot see or rewrite it (live test asserts typeof window.__jevBrowser === "undefined" from the page).
  • Loopback URLs only by default. --allow-host widens per host. If a click leaves the allowed origin (sign-in redirect, external link), the agent returns to the last good URL, tells Jev which action caused it, and blocks after three such trips.
  • Secrets: the log shows (secret); after a secret is typed, every later snapshot is scrubbed before Jev, the text model, or the log sees it. Password inputs never expose their value ((filled)).
  • Page text reaches Jev and the text model as untrusted data. Instructions say so explicitly.
  • Chromium runs a throwaway profile. Sandboxed launch first; --no-sandbox only when Chromium reports "No usable sandbox" (user namespaces disabled). The ready line reports sandbox: true|false.

Key patterns (learned from jev-ultrafast)

  • Speculative fan-out: one request asks "which operation?" and "which target for CLICK/TYPE_TEXT/SELECT?" at once. Unused heads are discarded.
  • One read per cycle: observe runs snapshot.js once. Jev sees that snapshot.
  • Semantic freshness guards: act compares page_key + the target's guard (value, enabled state, position, nearby text) for targeted actions, or the page marker for scroll/wait. A stale page returns stale: true; the loop re-observes without a stall penalty, capped at STALE_LIMIT (5).
  • Decision consumed before mutation: the log entry is written before act, so a navigation cannot erase the record.
  • Independent verification: DONE is a claim. jev-browser-verify.py runs as a separate question set; a rejected DONE goes back into history so Jev re-decides with that evidence. Three rejected DONEs mean BLOCKED.
  • Full distributions logged: every step records operation_probabilities and target_probabilities.
  • Text reuse only on identical context: cached by (url, target, label, current value).
  • Transient Jev errors retry as WAIT up to STALL_LIMIT (3); unavailable blocks at once.
  • Low-confidence picks are held: a non-DONE operation under LOW_CONFIDENCE (0.45) is not executed; the loop re-observes and counts toward the stall guard.
  • Settle before judging: observe waits for the DOM to be quiet (600 ms, capped at 3 s) and reports quiet; WAIT pauses 1.5 s then settles up to 8 s; a rejected DONE triggers a WAIT before the next decision. Jev sees page.settled and history notes when content was still changing.
  • Whole-page element table: rendered controls below the fold are offered too, marked offscreen; the driver scrolls them into view. Covered controls (modal backdrop, sticky header) are dropped at snapshot time, so an open modal leaves only its own controls.
  • Links say where they go: navigates away to /path or leaves this site, and decide's rules forbid them unless the goal names that page.

Text value selection

Order for a TYPE_TEXT target:

  1. --secret-env match on the field label.
  2. Program extracts candidate literals from the goal (quoted strings, emails, username X, search for X, numbers).
  3. Jev Choice over candidates plus NONE. Accepted at confidence >= 0.5.
  4. LLM via Anthropic Messages API (urllib, no SDK). Strict {"text": "..."} reply.

The text model writes one value. It never picks actions or judges progress.


Phase 1: OBSERVE

observe evaluates snapshot.js in the isolated world. Output:

[1] heading  Sign in                          []
[2] textbox  Username                         [CLICK, TYPE_TEXT]
[3] combobox Country (value=USA)              [SELECT]   options 3:1 USA, 3:2 Canada
[4] checkbox Remember (checked=False)         [CLICK]
[5] button   Sign in                          [CLICK]

Plus actions (e2:fill, e3:sel:ca, scroll_down, wait), page_key, guards, marker, and page text (<= 6000 chars).

Gate: snapshot captured and scrubbed. Phase 2.

Phase 2: DECIDE

jev-browser-decide.py returns operation, target, confidence, needs_text, and both probability maps. Invalid targets resolve to BLOCKED. Jev unavailable resolves to BLOCKED with source: unavailable.

Gate: operation and target decided and logged. Phase 3.

Phase 3: EXECUTE

  1. Resolve the observed action by (kind, index). Missing action: record, count toward stall.
  2. TYPE_TEXT: pick text per the order above.
  3. act with the snapshot's page_key, guards, marker. Stale: re-observe.
  4. Driver settles: two animation frames or 50 ms; combobox fills wait up to 200 ms for visible options.

Gate: action executed. Phase 4.

Phase 4: VERIFY

  • DONE: jev-browser-verify.py with deterministic checks. Verified: stop done. Rejected: history entry, re-decide.
  • BLOCKED: stop.
  • Stall guard: STALL_LIMIT (3) consecutive non-WAIT actions with an unchanged marker: stop blocked.
  • Budget: MAX_STEPS 60, MAX_REQUESTS 120.

Gate: loop or stop. Every exit carries reason.


Long tasks: checkpoint search

The loop above picks every step with Jev. For tasks longer than a few steps, use checkpoint search: an LLM or the caller sets subgoals, and Jev beam-searches between them (../../meta/building-with-jev/references/composition-patterns.md, Checkpoint search; scripts/jev_search.py). Branching needs a way back to a kept state (re-navigate to the checkpoint URL and replay); count that cost. The agent loop does not run checkpoint search yet. Adopt it only after this eval:

| Arm | Planner | Step picker | |---|---|---| | a | LLM plans every step | LLM | | b | none | Jev picks every step (current loop) | | c | LLM sets checkpoints | Jev beam search between them |

  • Run the same task set through all three arms, bucketed by task length (for example 1–5, 6–15, 16+ steps).
  • Report per bucket: success rate (verified DONE), total tokens (Jev plus LLM), and wall time.
  • Price and pace the eval per rule 7 of the production rules; use a held-out task set for the final report.

Request sizing and retries

Apply Jev production rules when you change the decide, text, or verify calls:

  • Keep each request at or under the reliable size from `python3 scripts/jev-size-probe.py --pay

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars425
CategoryAutomation
Updated1d ago
Forks48

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions