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Picks the next click or typed field toward a UI test goal, while your agent runs it. Early and lightly tested, so use it on test sites.
Free
Browser Nav
Example session with this skill installed
Use browser-nav to sign in as admin and open the settings page on my local test app, one step at a time.
- Read your context and instructions
- Compiled the browser nav
Summary
Goal reached in
5 calls: type the email, type the password, click Sign in, click Settings, then done. Your agent runs each step in the browser and reports pass.
This is real output from the packaged skill, driven over a scripted, made-up login flow (a login page, a dashboard and a settings page). For this run I pointed the skill at a tiny local stand-in that just works through Email, Password, Sign in and Settings in order. It shows the call format and the step loop. It says nothing about how a real model picks steps on a real site.
What each call returned
step 1 exit=0 {"action": "type", "ref": "ref_1", "p": 0.9}
step 2 exit=0 {"action": "type", "ref": "ref_2", "p": 0.9}
step 3 exit=0 {"action": "click", "ref": "ref_3", "p": 0.9}
step 4 exit=0 {"action": "click", "ref": "ref_7", "p": 0.9}
step 5 exit=0 {"action": "done"}
The same run, step by step
| Step | Page | Elements it was shown | Skill said | Your agent does |
|---|---|---|---|---|
| 1 | /login | Email, Password, Sign in, Forgot password | type ref_1 | types the email you gave it |
| 2 | /login | same | type ref_2 | types the password you gave it |
| 3 | /login | same | click ref_3 | clicks Sign in |
| 4 | /dashboard | Settings, Reports, Sign out | click ref_7 | clicks Settings |
| 5 | /settings | Display name, Save | done | checks the page and reports pass |
Next steps
- Pass the current
urland yourhistoryon every call, or a finished goal can look unfinished. - If it says
unsureorerror, pick the step yourself. - If it says
blocked, stop and report fail with the last page state. - Never let it submit payments or destructive actions without asking you first.
Connects securely to your tools. The creator never sees your data.
About this skill
Hey! This is a small helper for testing multi-step UI flows, like "sign in as admin and open settings" or a role-based access check.
You tell it your goal and hand it the page's interactive elements (role and name for each). It tells you the single next step: click this, type into that, you're done, or you're stuck. Your own agent does the clicking with its browser tool and gives the final pass or fail. At most 25 steps.
The loop
- Read the page's interactive elements with your browser tool.
- Pipe a small JSON request (goal, url, elements, history) into the script.
- Act on the answer:
click: click that element.type: focus that element and type what the goal calls for. It never invents text, and credentials come from you.done: check the goal on screen and report pass.blocked: stop and report fail with the last page state.unsureorerror: it is not confident or unavailable, so choose the step yourself.
- Add what you did to
historyand repeat.
It does not control a browser by itself. You need an agent with a browser tool (for example Claude in Chrome or Playwright).
Modes, and what is sent
- Model mode (optional). With a free Codiv OpenJev API key as
OPENJEV_API_KEY, or a local model set up withjev-tools-setup, a small decision model picks the step. It is sent the goal, the page URL, your last 8 actions and the elements' roles and names (up to 200), toapi.codiv.aior a loopback address for a local model. Secret-shaped strings are redacted first and the key is only ever sent to those hosts. Don't point it at pages showing private data. - No key. It returns
unsurewith the element whose name shares the most words with your goal, as a hint only, orerrorif nothing matches. Nothing is sent anywhere.
What you need
Python 3.10+. Standard library only, nothing to install.
Honest limits
- This is early. It was tested on one synthetic login page, five steps for "sign in as admin and open the settings page" (type email, type password, click Sign in, click Settings, then done). An earlier run said
blockedon the final page because the model's goal-met score wobbled between identical calls; the rule that "nothing left to click and the goal probably met" counts as done came from that. It has never been run against a real browser session. Treat every step as a suggestion. - Pass the current
urland recenthistory, or a finished goal can look unfinished. - Answers vary slightly between identical calls.
- Never submit payments or take destructive actions without asking the user.
- It appends one small line per model call (timestamp, number of questions, milliseconds, tokens, or an error type) to
~/.jev-tools/log.jsonl, or to the path inJEV_LOG. Page content and keys are never logged.
Part of jev-tools
One of several skills from the free, MIT-licensed jev-tools project: github.com/Rcidshacker/jev-tools
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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Requires
Codiv
Python