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Avaliar agentes de navegador em tarefas web repetíveis do Playw…

Execute um conjunto de avaliações repetíveis para agentes de navegador usando snapshots estáticos de tarefas web, em vez de julgá-los por demonstrações ou testes isolados.

O que é Avaliar agentes de navegador em tarefas web repetíveis do Playw…?

Este skill permite que desenvolvedores e usuários de agentes de IA realizem avaliações sistemáticas e repetíveis de agentes de navegador (browser agents) usando o Bananalyzer. Em vez de confiar em demonstrações manuais ou testes únicos, ele executa um conjunto de testes baseado em pytest contra snapshots estáticos de tarefas web, garantindo consistência e comparabilidade entre diferentes execuções. O skill é voltado para ambientes Python com Playwright e exige que o usuário implemente uma classe AgentRunner personalizada que recebe o exemplo de tarefa e um contexto do navegador Playwright para concluir a ação. Suporta a construção de um conjunto diversificado de sites para generalização do agente e planeja oferecer métodos de avaliação mais complexos no futuro. A ferramenta de linha de comando (CLI) 'banana-lyzer' constrói dinamicamente uma suíte de testes pytest a partir dos exemplos definidos, facilitando a automação da validação.

Funciona com~Claude Code~Codex CLI~Cursor

npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/benchmark-browser-agents-on-repeatable-playwright-web-tasks-with-bananalyzer

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Documentação

Avaliar agentes de navegador em tarefas web repetíveis do Playwright com Bananalyzer

Execute um conjunto de avaliações repetíveis para agentes de navegador usando snapshots estáticos de tarefas web, em vez de julgá-los por demonstrações ou testes isolados.

Pré-requisitos

Ambiente Python, runtime do navegador Playwright, execução de testes baseada em pytest, implementação de AgentRunner personalizada, exemplos de snapshots de tarefas web

Instalação

Requisitos e observações do upstream:

site individual. Para que um agente generalize bem, é necessário construir um conjunto diversificado de sites da web
No futuro, ofereceremos suporte a métodos de avaliação mais complexos e exemplos que exijam várias etapas para serem concluídos.

Notas de uso básico ou primeiros passos:

Banana-lyzer é uma ferramenta de linha de comando que executa um conjunto de avaliações em um conjunto de sites de exemplo.
A ferramenta CLI executa sequencialmente os exemplos em um agente definido pelo usuário, construindo dinamicamente uma suíte de testes pytest.
AgentRunner expõe o exemplo e um contexto do navegador Playwright para uso.
Fonte: https://github.com/reworkd/bananalyzer
Extraído da documentação upstream: https://raw.githubusercontent.com/reworkd/bananalyzer/HEAD/README.md

Documentação

https://github.com/reworkd/bananalyzer

Fonte

Agent Skill Exchange

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

Academic Paper Citation Network Mapper

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ACF Extended for Advanced Custom Fields Workflows

An ASE skill built around ACF Extended, the WordPress enhancement suite for Advanced Custom Fields that adds field types, admin improvements, front-end forms, options pages, and developer tooling. It is a practical fit for agents working inside complex WordPress content models and custom field workflows.

ACF to Gutenberg Block Migrator

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Activepieces Open Source Workflow Automation

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ActivityWatch Cross-Platform Automated Time Tracker and Producti

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act Local GitHub Actions Runner

act is an open-source CLI tool that runs GitHub Actions workflows locally using Docker, enabling fast feedback on workflow changes without pushing to GitHub. It is a standard tool for local Actions development and testing.

Add a browser review checkpoint before risky agent actions with

Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.

Add Claude design-system and accessibility workflows with UX/UI

Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.

Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.

Add managed long-term memory to LangGraph agents with LangMem

Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.

Add multimodal lifelong memory to MCP and Python agents with Sim

Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.

Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

Adobe Firefly API Batch Image Generator

Calls Adobe Firefly

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