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browser/docs/agent.md
Adrià Arrufat 2d2914e878 agent: add /usage slash command to REPL
Adds a new `/usage` meta command to print cumulative token usage and
cache hit rate for the current session. Also updates zenai.
2026-06-05 13:35:34 +02:00

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Agent mode

lightpanda agent turns Lightpanda's headless engine into a browsing agent you can talk to in plain English, script deterministically, or drive from your own LLM. There's no rendering and no images — it reasons over pages as text, which makes browsing fast and cheap to automate.

New here? The tutorial walks you from a fresh build to a recorded, replayable Hacker News scraper in a few minutes. This page is the reference: every flag, slash command, and browser tool. For the JavaScript script format, see agent-script.md.

lightpanda agent can act as:

  • an LLM agent that drives the browser with tool calls (--provider),
  • a scripted runner that runs a recorded .js script deterministically,
  • a basic REPL for hand-driven slash commands with no LLM at all,
  • a one-shot task runner that prints a single answer to stdout (--task).

All four modes share the same browser tools (goto, click, fill, tree, markdown, search, ...). The same set is exposed over MCP via lightpanda mcp, so an agent script and an MCP client see the same surface — that is also the way to drive Lightpanda from an external LLM agent (Claude Code, etc.) without giving Lightpanda its own API key.

Quick start

# Interactive REPL — auto-detects an API key from your environment
./lightpanda agent

# Force a specific provider
./lightpanda agent --provider anthropic

# Basic REPL (no LLM, slash commands only)
./lightpanda agent --no-llm

# Run a saved script, then exit
./lightpanda agent session.js

# One-shot: ask a question, capture the answer on stdout
./lightpanda agent --task "what is on the front page of hn?"

# See which models the resolved provider offers
./lightpanda agent --list-models

Providers and API keys

Provider Flag API key env
Anthropic --provider anthropic ANTHROPIC_API_KEY
OpenAI --provider openai OPENAI_API_KEY
Gemini --provider gemini GOOGLE_API_KEY or GEMINI_API_KEY
Ollama --provider ollama none (local)

Defaults: --model falls back to a sensible per-provider default; in the REPL, /provider <name> and /model <name> change the current selection (Tab completes the candidates). --base-url overrides the API endpoint (Ollama defaults to http://localhost:11434/v1). Run --list-models to see exactly what the resolved provider offers, --system-prompt to swap in your own system prompt, and --verbosity <low|medium|high> to tune how much progress detail goes to stderr (--task defaults to low, or high when stderr is piped/redirected so harnesses capture the full [tool/result] trace).

--effort <none|minimal|low|medium|high|xhigh> sets the per-turn reasoning budget for thinking models (it maps to each provider's native thinking / reasoning-effort knob and is ignored by non-thinking models). The interactive REPL defaults to low so turns stay snappy; --task and script runs default to medium, where answer quality matters more than per-turn latency. Higher effort can reduce the number of tool calls by planning better, so it's a real tradeoff rather than a pure slowdown. Change it live with /effort; the selection is remembered in .lp-agent.zon.

--model is validated against the provider's catalog up front: an unknown name fails fast with a pointer to --list-models rather than erroring mid-task. For Ollama, the default model is checked against what's actually pulled — if it's missing, the agent falls back to the first installed model (an explicit --model that isn't installed errors instead, with an ollama pull hint).

Provider auto-detection

When --provider is omitted, lightpanda picks one in this order. The REPL shows the resolved model and effort level in its status bar; the multi-key picker and any fallback notices (e.g. an Ollama default that isn't installed) print to stderr:

  1. Remembered → the provider/model you last selected with /provider or /model (plus the /effort level), persisted per-directory in .lp-agent.zon, as long as its key is still set.
  2. Auto-detected → otherwise the first key found in priority order (ANTHROPIC_API_KEYGOOGLE_API_KEY/GEMINI_API_KEYOPENAI_API_KEY). If several keys are set and you're in an interactive REPL, the agent prompts you to choose; non-interactive runs (--task, pipes, --list-models) take the first. Switch any time with /provider, or override with --provider.
  3. Local Ollama → if no cloud key is set, the agent probes a local Ollama server (http://localhost:11434/v1, or --base-url) and uses it when it answers with at least one pulled model.
  4. No provider at all → falls back to the basic REPL (slash commands only). Natural language and the LLM-driven commands (/login, /logout, /acceptCookies) will reject.

--no-llm is the explicit bypass: it forces the basic REPL even when an API key is present or --provider is set. Use it to test slash commands without burning tokens, or to disable the LLM in a saved command without editing the existing flags. --no-llm wins over --provider.

REPL Slash Commands

The REPL uses a tiny slash-command language for browser actions. Each command is /<tool> [args], a # comment, or blank. There is no other syntax in basic REPL mode: anything that doesn't match those three forms is a parse error.

Slash commands accept any of:

  • a single positional value, when the tool has exactly one required field — /goto 'https://example.com', /extract '{"karma":"#karma"}';
  • key=value pairs — values may be bare or quoted; strings with whitespace must be quoted (/fill selector='#email' value='user@x.com');
  • a raw {json} blob — handed straight to the tool (/findElement {"role":"button"}).

Tools whose selector is optional (e.g. /click, /hover, /findElement) have zero required fields, so they don't take a positional and must be written as key=value: /click selector='a.login', not /click 'a.login'.

Quoting is content-aware: '…', "…", and triple-quoted '''…''' / """…""" for values that mix both quote styles or span multiple lines. Recorded JavaScript scripts use the equivalent function-call form instead of slash lines.

Two slash commands have no underlying tool — they trigger an LLM turn that the agent translates into actual tool calls:

Command Notes
/login LLM-driven: fills credentials from $LP_* env vars.
/logout LLM-driven: find the logout control and sign out.
/acceptCookies LLM-driven: dismiss the consent banner.

All three require an LLM. --no-llm rejects them.

In the REPL (and only the REPL), a line that isn't a slash command and doesn't start with # is sent to the LLM as a natural-language prompt. To leave the REPL, use the /quit meta command.

Example script

# Log into the demo and grab the dashboard title and visible cards.
# Site-scoped vars (LP_<SITE>_<FIELD>) avoid collisions when you have
# credentials for several sites; the unprefixed form is the fallback.
/goto 'https://demo-browser.lightpanda.io/'
/acceptCookies
/fill selector='#email' value='$LP_DEMO_USERNAME'
/fill selector='#password' value='$LP_DEMO_PASSWORD'
/click selector='button[type="submit"]'
/waitForSelector '.dashboard'
/extract '{"title": ".dashboard h1", "cards": [".dashboard .card .name"]}'

/extract takes a JSON schema object — each value tells the extractor what to lift off the page, and the whole result is printed to stdout as a single JSON object. Supported value forms:

  • "<sel>"textContent.trim() of the first match (string or null).
  • "" — the matched element's own text (only inside a fields block).
  • ["<sel>"] — text of every match (string array). Sugar for [{"selector": "<sel>"}].
  • {"selector": "<sel>", "attr": "<name>"} — attribute of the first match.
  • [{"selector": "<sel>", "fields": {…}}] — array of records, each fields value resolved relative to the matched element.
  • Add "limit": N inside any array's object spec to cap matches at N (works for text, attribute, and fields shapes — e.g. [{"selector": ".story .title", "limit": 5}] for top 5 titles).

Use /extract '''…''' (or """…""") to spread a schema across multiple lines. The schema is parsed in Zig before the page-side walker runs, so a malformed schema is rejected up front with a plain Error: InvalidParams rather than a V8 stack trace. See agent-tutorial.md section 3 for a worked example against Hacker News.

Cross-call state with lp.*

/extract and /evaluate each return one value per call, but real scrapes often need to carry data forward — capture a list on one page, then walk it across navigations. Two primitives keep that simple.

save=<name> on /extract or /evaluate stashes the result in a Session-scoped store keyed by <name> instead of dumping it to stdout. The stored value is then exposed to every subsequent /evaluate as globalThis.lp.<name>:

/goto 'https://news.ycombinator.com/'

/extract save=front '''
{
  "stories": [{
    "selector": "tr.athing",
    "limit": 5,
    "fields": {
      "id":    {"attr": "id"},
      "title": ".titleline > a"
    }
  }]
}
'''

/evaluate '''
console.log(lp.front.stories[0].title);
'''

save=d commands print nothing on success so scripts pipe cleanly.

Auto-sync. Any mutation of lp.* inside an /evaluate is persisted at the end of the call. Adding a key (lp.x = …), updating a nested value (lp.front.stories[0].comments = […]), or removing a key (delete lp.x) all propagate to the store. The next /evaluate sees the update — even after a navigation, because the store lives Session-side, not on the page.

List → detail. A common scrape captures a list, then visits each row for more data. Capture the list with /extract save=<name>, then loop in /evaluate: read lp.<name>, goto each row's URL, and extract the detail — /evaluate's top-level await and full JS make the round-trip explicit.

Async evaluate. When a scrape needs logic /extract can't express, /evaluate is the escape hatch: top-level await works directly — the body runs as an async function, so use return to produce a value. runEval pumps the event loop until it settles, then surfaces the resolved value (or the rejection as an error). A body with no explicit return resolves to undefined, which evaluate treats as silent. Returned objects and arrays are serialized to JSON automatically, so no JSON.stringify is needed.

The store is script-run scoped: it's bound to the Session that runs the script, and goes away when that Session does. There is no cross-session persistence; if you need that, use localStorage (which is origin-scoped and persists across navigations within a session).

Saving and loading

From the REPL, /save [file.js] writes the session back to a .js file and /load <path> runs a script from disk against the current session.

/save works one of two ways. With --no-llm it transcribes the session deterministically: state-mutating commands (/goto, /click, /fill, /scroll, /hover, /selectOption, /setChecked, /waitForSelector, /waitForScript, /press, /evaluate, /extract) become JavaScript calls, read-only commands (/tree, /markdown, /links, /findElement, …) are dropped, and each natural-language prompt that produced recorded actions is written as a // <prompt> comment above those calls so the script stays readable. With an LLM it instead synthesizes an idiomatic script from the whole session — the synthesis prompt asks for JavaScript only ("no commentary"), so the result generally has no such comments: the model folds intent into the code and drops dead-ends.

JavaScript Script Running

./lightpanda agent script.js runs without making any LLM call. Agent scripts are plain synchronous JavaScript plus the installed Lightpanda primitives:

goto("https://example.com");
click({ selector: "a.login" });
evaluate("document.title");

The script runs in an agent-only V8 context. It has no window, document, or DOM APIs. Browser interaction happens only through the installed primitives (goto, click, fill, evaluate, extract, and the other recorded browser actions). The primitives are synchronous and blocking — each returns its result directly, so write const data = extract(…), not await extract(…). There is no async/await/Promise contract around them. (evaluate(...) can run async JS inside the page, but the evaluate(...) call itself still returns synchronously.) It is not Node.js either: there is no require, process, fs, npm package loading, or Node standard library. The evaluate(...) primitive executes its string in the current page context; page scripts cannot see agent variables or agent primitives.

Tool errors throw JavaScript exceptions and stop execution. See agent-script.md for the full script format reference.

REPL features

  • Status bar: a line under the prompt shows the active model and quick hints (! JS, Tab completes, /help); in --no-llm it reads basic REPL — slash commands only. It drops the least-important segments first when the terminal is narrow.
  • JS mode (!): type ! on an empty prompt to toggle a scratchpad where the whole line runs as page-side JavaScript — the same context as evaluate, so document and window are in scope. Handy for poking at a page without wrapping every line in /evaluate. $LP_* refs are still resolved at execution, console output is echoed back, and Esc exits. JS-mode lines are not recorded.
  • Tab completion (case-insensitive): cycles through /<tool> and meta slash commands. The dim grey suffix shown after the cursor is the first match.
  • Persistent history: stored in .lp-history in the working directory.
  • Meta slash commands: /help lists tools (/help <tool> prints the JSON schema), /provider [name] and /model [name] change the active provider/model — Tab after the space completes from detected providers and the provider's fetched model list, and bare /provider//model print the current selection — /save [file.js] writes the session to a script and /load <path> runs one from disk (Tab completes file paths), /quit exits the REPL, /verbosity <low|medium|high> tunes the log level, /effort <none|minimal|low|medium|high|xhigh> sets the per-turn reasoning budget (saved to .lp-agent.zon), and /usage prints cumulative token usage and the cache hit rate for the session. These are REPL-only and never recorded.
    > /goto https://example.com
    > /findElement role=button name=Submit
    > /evaluate {"script": "document.title"}
    > /quit
    
  • Stdout vs stderr: the final assistant answer and data-producing slash commands (/extract, /evaluate, /markdown, /tree, …) write to stdout. Tool calls, progress, and errors go to stderr, so lightpanda agent --task ... > out.txt captures a clean answer.

One-shot mode (--task)

./lightpanda agent --provider gemini \
  --task "what is the top story on news.ycombinator.com?"

--task runs a single user turn, prints the final answer on stdout, and exits. Combine with -a <path> / --attach <path> (repeatable) to feed local files to providers that accept attachments. Text files are inlined into the prompt (max 512 KiB each); binary files (image/*, audio/*, pdf) are base64-encoded inline (max 20 MiB each). Unsupported MIME types error out before any browser work runs.

Driving Lightpanda from an external LLM agent

When the calling agent already has its own LLM (e.g. Claude Code), use lightpanda mcp rather than lightpanda agent. The MCP server exposes the same browser tools (goto, click, fill, ...) listed below, so the external agent does the planning while Lightpanda only drives the browser. No --provider or API key is required on the Lightpanda side.

{
  "mcpServers": {
    "lightpanda": {
      "command": "/path/to/lightpanda",
      "args": ["mcp"]
    }
  }
}

Tool names are camelCase and case-sensitive — there are no aliases. MCP clients must call the canonical tags (goto, evaluate, tree, save, …).

For sub-task delegation in the other direction — calling Lightpanda's own LLM-driven agent in a one-shot fashion — use --task on stdin instead.

Saving a script over MCP

lightpanda mcp exposes a save tool so an external agent can persist the session as a .js script for later deterministic replay. Unlike the standalone agent's /save, the MCP server has no LLM of its own — the calling client holds the conversation, so it synthesizes the script and passes it in:

Tool Args Effect
save { path: string, script: string } Write script to path (relative, no ..; created or overwritten) and return the absolute location and line count.

The tool's description carries the same synthesis guidance the agent's /save gives its LLM: prefer the builtins you called as tools (goto, click, fill, extract, …) as JavaScript calls, drop dead-ends, and keep $LP_* placeholders. Any literal LP_* value is scrubbed back to its placeholder before the file is written. The result runs without an LLM via ./lightpanda agent session.js.

Browser tools

The agent and MCP server share the tool set defined in src/browser/tools.zig. Highlights:

  • goto, search (Tavily when TAVILY_API_KEY is set, DuckDuckGo otherwise)
  • tree, markdown, html, links, interactiveElements, structuredData, detectForms, nodeDetails, findElement
  • click, fill, hover, press, scroll, selectOption, setChecked, waitForSelector, waitForScript
  • extract (the schema-driven data tool), evaluate, consoleLogs, getUrl, getCookies, getEnv

Selectors prefer CSS over backendNodeId for the click-family tools, since node IDs are invalidated by any DOM mutation. The system prompt enforces this for the LLM.

Security notes

  • The agent treats page content as untrusted data, not instructions. URLs surfaced by a page are not followed unless they match the user's task.
  • $LP_* environment variable references in /fill values are resolved at execution time inside the subprocess, so credentials never enter the LLM context. Conventional naming for site-scoped values is LP_<SITE>_<FIELD> (e.g. LP_HN_USERNAME, LP_GH_TOKEN); the unprefixed LP_USERNAME / LP_PASSWORD form is the generic fallback.
  • The getEnv tool only reads variables whose name starts with LP_. Everything else (provider API keys, system env, third-party secrets) reports "not set" so the model can't probe for it. The user controls what lives under LP_*. Note that getEnv returns the value to the model — fine for non-secret config like base URLs, but never call it on credentials (use $LP_* placeholders in fill values instead).
  • --obey-robots, --http-proxy, --user-agent, and the rest of the browser-level CLI flags apply to agent the same way they apply to serve, fetch, and mcp.
  • REPL prompts are persisted to .lp-history in the current working directory in plaintext (no encryption). Anything you type at the prompt — including natural-language context that accompanies a /login — lands in that file. Delete it or move out of sensitive directories if you don't want it retained.
  • save rejects empty, absolute, and .. paths, but does not follow up on symlinks. On a shared filesystem, a pre-existing symlink at the target would be written through to whatever it points at. Prefer a fresh directory you own when saving in untrusted environments.