This product was not featured by Product Hunt yet.
It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).

Product upvotes vs the next 3

Waiting for data. Loading

Product comments vs the next 3

Waiting for data. Loading

Product upvote speed vs the next 3

Waiting for data. Loading

Product upvotes and comments

Waiting for data. Loading

Product vs the next 3

Loading

Agentwall

Stop AI agents from running destructive calls unchecked

AI agents executing tool calls have no control point between model output and actual execution. Schema validation rejects malformed args — it can't decide whether DROP TABLE users should run right now. Agentwall adds that layer. Classifies each call as safe, cautious, or destructive. Destructive calls require approval before running. Every attempt is logged as JSONL. Rollback hooks compensate if a session fails. Python + TypeScript. Works with Anthropic, OpenAI, LangChain. Zero runtime deps.

Top comment

Hey PH 👋 I'm the builder. Built agentwall after running agents against real systems and realizing there was nothing between "model decides to call this" and "it runs." Frameworks assume if arguments pass schema validation the call should execute — but schema validation can't decide whether DROP TABLE users is appropriate right now. The design decision I'm least sure about: using regex rules on tool name and serialized arguments for classification. It's simple and deterministic but breaks on edge cases. Would love to know how people here are thinking about risk classification for tool calls. Happy to answer anything.

About Agentwall on Product Hunt

Stop AI agents from running destructive calls unchecked

Agentwall was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #117 on the daily leaderboard. AI agents executing tool calls have no control point between model output and actual execution. Schema validation rejects malformed args — it can't decide whether DROP TABLE users should run right now. Agentwall adds that layer. Classifies each call as safe, cautious, or destructive. Destructive calls require approval before running. Every attempt is logged as JSONL. Rollback hooks compensate if a session fails. Python + TypeScript. Works with Anthropic, OpenAI, LangChain. Zero runtime deps.

On the analytics side, Agentwall competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Agentwall performed against the three products that launched closest to it on the same day.

Who hunted Agentwall?

Agentwall was hunted by Afonso Pereira. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

For a complete overview of Agentwall including community comment highlights and product details, visit the product overview.