As a security professional, it is important to conduct a thorough reconnaissance. With the increasing use of APIs nowadays, it has become paramount to keep access tokens and other API-related secrets secure in order to prevent leaks. However, despite technological advances, human error remains a factor, and many developers still unknowingly hardcode their API secrets into source code and commit them to public repositories. GitHub, being a widely popular platform for public code repositories, may inadvertently host such leaked secrets. To help identify these vulnerabilities, I have created a comprehensive search list using powerful search syntax that enables the search of thousands of leaked keys and secrets in a single search.

(path:*.{File_extension1} OR path:*.{File_extension-N}) AND ({Keyname1} OR {Keyname-N}) AND (({Signature/pattern1} OR {Signature/pattern-N}) AND ({PlatformTag1} OR {PlatformTag-N}))

**1.

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In this post, I'll start from scratch and build up to OpenClaw's architecture step by step, showing how you could have invented it yourself from first principles, using nothing but a messaging API, an LLM, and the desire to make AI actually useful outside the chat window.

End goal: understand how persistent AI assistants work, so you can build your own (or become an OpenClaw power user).

When you use ChatGPT or Claude in a browser, there are several limitations:

Analyze trading snapshots from CSV to calculate P&L, win rate, and expected value metrics (Standard EV, Kelly Criterion, Sharpe Ratio) aggregated by ISO week. Pure functional core for calculations with console output.

• Load trade snapshots from CSV with type validation
• Calculate realized P&L by pairing ENTRY/EXIT events

1. Open aistudio.google.com — select Gemini 2.5 Pro
2. Paste everything below the line into the System Instructions field (or as your first message)

Date: 2026-02-11

How to build a complete AI collaboration system — from foundation to advanced patterns

These aren't separate tools to adopt. They're an evolved system where each layer depends on the one below it.

Layer 1 is the unlock. Without the right AI behavior — autonomous execution, collaboration over reminders, prototype-first — nothing else works. You can't have effective workflow if your AI waits for permission on every file. You can't have group primers if your AI doesn't maintain docs automatically.