brainstorming
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or planning anything new, in software or out of it (a talk, a business, a renovation).
core-web-agentBuild, run, debug, and cost-check LaVague WebAgent workflows with WorldModel, ActionEngine, PythonEngine, logging, and safe dry-run scaffolds.
Independent GitHub snapshot ยท Automated classification ยท Original documentation governs
Use this sub-skill when the task is to create, adapt, debug, or explain a LaVague WebAgent run loop: WorldModel, ActionEngine, PythonEngine, navigation controls, logging, token counting, and returned ActionResult handling.
WorldModel, ActionEngine, a browser driver, and WebAgent.agent.run(...), agent.run_step(...), agent.demo(...), or a dry-run template.ActionResult.success, ActionResult.output, generated code, logs, token/cost estimates, and debug node displays.../browser-drivers/SKILL.md.../contexts-and-retrievers/SKILL.md.AgentServer, DriverServer, or lavague-serve: use ../server-extension-gradio/SKILL.md.lavague-qa or lavague-test CLI workflows: use ../qa-and-test-runner/SKILL.md.pkg_resources failures, stale result/debug state, and core API misuse.la-vague skill root before spending browser or model-provider time:python sub-skills/core-web-agent/scripts/lavague_minimal_agent.py --dry-run
The helper validates imports and prints a runnable template by default. It does not start a browser, contact a model provider, browse the web, or write logs unless --run-live is explicitly supplied.
from lavague.core import WorldModel, ActionEngine
from lavague.core.agents import WebAgent
from lavague.drivers.selenium import SeleniumDriver
# Requires browser support and the default model-provider credentials.
driver = SeleniumDriver(headless=True)
action_engine = ActionEngine(driver)
world_model = WorldModel()
agent = WebAgent(world_model, action_engine, n_steps=5)
agent.get("https://example.com")
result = agent.run("Summarize the visible page")
print(result.success, result.output)
Before running a live objective, confirm the matching browser route and provider-context route. The default LaVague stack uses OpenAI-backed models and embeddings, so OPENAI_API_KEY is normally required unless you pass a custom context/model stack.
WorldModel.from_context(context) and ActionEngine.from_context(context, driver) when a provider context owns the LLM, multimodal LLM, and embedding choices.llm=, embedding=, mm_llm=, retriever=, or custom engines only when mixing components deliberately.agent.run_step(objective) for manual loops or debugging one instruction at a time.agent.run(objective, display=True) only when notebook/display output is useful and safe.agent.run(..., log_to_db=True) only when a local SQLite log file is acceptable.agent.demo(...) only after routing to the Gradio/server sub-skill because it imports lavague-gradio lazily.lavague.core, the selected driver package, and selected context package import.LAVAGUE_TELEMETRY=NONE is set if telemetry must be disabled.