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Agentbox

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gabrielgreco1
agentbox

Run web-scraping subagents inside isolated Docker sandboxes, one box per subagent. Each box has a terminal (curl, python), a persistent headless Chromium, passive request listeners that log every HTTP call, and an optional proxy with a hard budget and known cost per request. Use when a task fans out to several subagents that must browse or scrape websites, find hidden API endpoints behind pages, validate data sources or build crawlers, and you need every request and every agent step logged and auditable.

Overview

Publishergabrielgreco1
Repositoryskills
Skill nameagentbox
Stars
79
Forks
12
Bundled files
16
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 16 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by gabrielgreco1 on GitHub. Read the source before you install it.

Installation

Install the Agentbox AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/gabrielgreco1/skills/tree/main/agentbox
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/gabrielgreco1/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/agentbox .claude/skills/agentbox
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agentbox in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agentbox on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agentbox is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

agentbox

You are the orchestrator. For every subagent you spawn, you start one box (a Docker container) and hand its name to that subagent. The subagent keeps running on the host with its normal tools, but every web action goes through agentbox exec <box> -- <command>. Each box logs every request, every command and the agent's own journal, so you can check every claim a subagent makes before you report it.

orchestrator (you)
 ├─ subagent A ──docker exec──▶ box A: terminal · Chromium · listeners · proxy tunnel ──▶ proxy ──▶ website
 ├─ subagent B ──docker exec──▶ box B: …
 └─ subagent C ──docker exec──▶ box C: …
                                  └─ /work  ==  $AGENTBOX_HOME/runs/<box>/ on the host (logs, results)

When the skill is activated, do this in order

  1. Docker: read docker/01-preflight.md and run its checks. Stop and tell the user if Docker is missing or not running. Never install Docker yourself.
  2. Workspace and image: read docker/02-workspace.md. If the workspace is not installed (or its version is older than this skill's), materialize every file listed there from the folders below, then build the image (docker/03-image.md). The host CLI is in docker/04-cli.md.
  3. Proxy: read proxy/01-config.md. Make sure $AGENTBOX_HOME/config/proxy.json exists with the user's proxy services, the budget per box and the cost of each service. If it does not exist, ask the user for it (never invent credentials or prices). Boxes also work without a proxy, in direct mode only.
  4. Understand the moving parts before briefing anyone (read once per session, skim later):
    • proxy/02-routing.md: how traffic leaves the box, proxy on|off, budget enforcement.
    • listener/README.md: how requests are observed without touching them.
    • browser/browser.md: the persistent browser and its CLI.
    • logs/logs.md: what is logged, the agent journal, the timeline and the audit.
  5. Orchestrate: follow subagents/orchestrator.md. Brief each subagent with subagents/subagent-prompt.md, filled in, including the proxy cost table. The ladder subagents must follow is in subagents/escalation.md.
  6. Audit and report: when a subagent finishes, collect its transcript, build the timeline and check every claim against the request log (logs/logs.md, "Audit"). Only then report.
  7. Tear down: agentbox down <box> or agentbox down --all. Runs are kept on disk.

Folder map

FolderWhat it holds
docker/preflight checks, workspace layout, Dockerfile and image build, host CLI
proxy/provider-agnostic proxy config (credentials, budget, cost per service), the browser tunnel, proxy command, budget accounting
listener/shared logging library, browser listener (CDP), curl wrapper, python hook, reqlog
browser/Chromium boot flags and the browser command
logs/log files, agent journal, transcript import, timeline, claim audit
subagents/orchestrator procedure, subagent prompt template, escalation ladder

Rules that always apply

  • One box per subagent. Never share a box between subagents.
  • Listeners only observe. Nothing sits in the traffic path or decrypts TLS for logging.
  • The proxy is opt-in per box (proxy on) and capped by its budget. When the budget is spent, requests fail with HTTP 402. Costs are estimates from the configured prices; the provider's dashboard is the source of truth.
  • Never try to get past a login, a paywall or a CAPTCHA. Report what is blocked and what sits behind it.
  • Respect each site's terms and rate limits. Only scrape what the user is allowed to collect.
  • A subagent's "blocked" or "not available" claim counts only if the log shows the failure at every rung of the escalation ladder.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Agentbox AI skill do?

Run web-scraping subagents inside isolated Docker sandboxes, one box per subagent. Each box has a terminal (curl, python), a persistent headless Chromium, passive request listeners that log every HTTP call, and an optional proxy with a hard budget and known cost per request. Use when a task fans out to several subagents that must browse or scrape websites, find hidden API endpoints behind pages, validate data sources or build crawlers, and you need every request and every agent step logged and auditable.

Why use Agentbox on TypingMind?

Because you install it once and use it with any model. Agentbox is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agentbox in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gabrielgreco1/skills/tree/main/agentbox. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Agentbox?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agentbox?

As many as you like. As long as a model supports skills, you can use Agentbox with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agentbox AI skill free?

It is published on GitHub by gabrielgreco1. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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