islo-labs

islo-labs / doubleagent

Public

High-fidelity fakes of third-party services for AI agent development.

19
2
100% credibility
Found Feb 18, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

DoubleAgent creates realistic fake versions of APIs from services like GitHub, Slack, Stripe, and Auth0 to let developers test AI agents rapidly without rate limits, costs, or state issues.

How It Works

1
🔍 Discover DoubleAgent

You hear about DoubleAgent, a handy tool that lets you test AI helpers with pretend versions of popular services like email, chat, or payments without real limits or bills.

2
📥 Get the tool

You grab the free tool with a simple download that puts a friendly command on your computer.

3
🛒 Pick your services

You choose which pretend services you need, like chat apps or code storage, and add them to your project.

4
🚀 Start the fakes

With one command, you launch isolated pretend services on your computer that act just like the real ones but run lightning-fast.

5
🔗 Connect your helpers

You point your AI helpers or tests to these local pretend services, and they work perfectly with your usual tools.

6
🔄 Reset anytime

When you need a fresh start, you wipe the slate clean or load sample data in seconds.

🎉 Test freely

Now you run dozens of AI helpers in parallel, iterate super quickly, and save time and money without any cleanup hassles.

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AI-Generated Review

What is doubleagent?

DoubleAgent creates high-fidelity fakes of third-party services like GitHub, Slack, Auth0, Stripe, and Descope for AI agent development. You install via a simple curl script that works on Mac and Linux, then use the Python-compatible CLI to add services (doubleagent add github slack), start them on local ports (doubleagent start github --port 9000), and point official SDKs at localhost URLs via env vars. It eliminates rate limits, API costs, state collisions, and cleanup hassles when running dozens of agents in parallel.

Why is it gaining traction?

Unlike basic mocks with static responses, these fakes maintain real state—create a repo or user, and it's there for later retrieval or deletion—and pass contract tests against live APIs using official SDKs like PyGithub or stripe-python. Webhook support auto-dispatches events, and one-command resets/seeds keep iterations blazing fast with ms responses. The doubleagent download and setup just works across arches, no Docker needed.

Who should use this?

AI agent builders testing GitHub issue workflows, Slack bots, Stripe payments, or Auth0 logins without burning real quotas. Teams doing parallel agent sims in dev environments, especially those hitting double agent port not valid errors from port conflicts. Python devs prototyping multi-service agent flows locally.

Verdict

Grab it if you're in AI agent development—early wins on high-fidelity GitHub and Slack fakes make it a dev accelerator despite 12 stars and 1.0% credibility score. Still maturing with more services incoming; pair with doubleagent contract for confidence before prod sims. (198 words)

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