Release: "sentinel-ir@0.1.2 on npm" (https://www.npmjs.com/package/sentinel-ir/v/0.1.2)
Source: "GitLab repository" (https://gitlab.com/jakubrojicek11/sentinel-ir)
Release changes: "Compare v0.1.1 with commit adf875a1" (https://gitlab.com/jakubrojicek11/sentinel-ir/-/compare/v0.1.1...adf875a1502e3bcf7242bff85a32dcf62f023c07)
Most people building AI agents today make the same expensive mistake: they feed raw, chaotic source code directly into the LLM.
It’s like driving to the supermarket, buying raw ingredients, and cooking for hours every time you want a quick snack. It is incredibly SLOW, expensive, and the AI often gets lost in the recipe.
That’s why I created Sentinel-IR.
What is Sentinel-IR?
Think of it not as an antivirus, but as a Context Extraction Engine.
Instead of forcing your AI Chef to read thousands of lines of code to find security risks or analyze structures, Sentinel-IR pre-processes the code into a clean, structured "Menu."
• The Problem Today: You ask the LLM: "Is this 10,000-line code safe?" The LLM burns through millions of tokens, cooks the server, and takes minutes to answer.
• The Sentinel-IR Way: Our AST analyzer strips out the garbage and delivers a precise, lightweight Intermediate Representation (IR).
How it works at the table:
When the LLM Chef gets the Sentinel-IR Menu, it doesn't need to invent a recipe. It instantly reads the order:
• 🪑 Table 10 wants a strong drink (child_process.execSync).
• 🚫 Special request: But hold the pickles! (The analyzer caught an attacker trying to hide a malicious payload inside a parenthesized_expression).
Why it matters:
By giving the LLM a clean, structured semantic extract instead of raw text, your AI agents make security and logic decisions in milliseconds instead of minutes—saving you a massive fortune on OpenAI token bills.
Sentinel-IR is now live on npm (v0.1.2). Let's make AI agents fast again.
Top comments (0)