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dipampaul17
AgentGuard
JavaScript2025–2025
dipampaul17 / AgentGuard

AgentGuard

Real-time guardrail that shows token spend & kills runaway LLM/agent loops.

3Distinct people
3Mentions
1Explicit recommenders
174GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Real-time guardrail that shows token spend & kills runaway LLM/agent loops.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

> [1] https://github.com/dipampaul17/AgentGuard/commit/d49b361d7f3... It's kind of crazy that people use these multi-billion parameter machine learning models to do…

diggan used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by hour3 dated mentions

Observed mentions: 2025-07-31 05:54:04 UTC to 2025-07-31 11:17:14 UTC.

012025-07-31 05:00:00 UTC to 2025-07-31 06:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsJul 31, 05:002025-07-31 06:00:00 UTC to 2025-07-31 07:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-07-31 07:00:00 UTC to 2025-07-31 08:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-07-31 08:00:00 UTC to 2025-07-31 09:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJul 31, 08:002025-07-31 09:00:00 UTC to 2025-07-31 10:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-07-31 10:00:00 UTC to 2025-07-31 11:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-07-31 11:00:00 UTC to 2025-07-31 12:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJul 31, 11:00

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jul 31, 05:002025-07-31 05:00:00 UTC2025-07-31 06:00:00 UTC110
Jul 31, 06:002025-07-31 06:00:00 UTC2025-07-31 07:00:00 UTC000
Jul 31, 07:002025-07-31 07:00:00 UTC2025-07-31 08:00:00 UTC000
Jul 31, 08:002025-07-31 08:00:00 UTC2025-07-31 09:00:00 UTC000
Jul 31, 09:002025-07-31 09:00:00 UTC2025-07-31 10:00:00 UTC101
Jul 31, 10:002025-07-31 10:00:00 UTC2025-07-31 11:00:00 UTC000
Jul 31, 11:002025-07-31 11:00:00 UTC2025-07-31 12:00:00 UTC101

What Hacker News says

3 sources
diggan·Jul 31, 2025Recommendation phrase
> [1] https://github.com/dipampaul17/AgentGuard/commit/d49b361d7f3... It's kind of crazy that people use these multi-billion parameter machine learning models to do search/replace of words in text files, rather than the search/replace in their code editor. I wonder what the efficiency difference is, must be 1000x or even 10000x difference? Don't get me wrong, I use LLMs too, but mostly for things I wouldn't be able to do myself (like isolated math-heavy functions I can't bother to understand the internals of), not for trivial things like changing "test" to "step" across five files. I love that the commit ends with > Codebase is now enterprise-ready with professional language throughout Like "enterprise-ready" is about error messages and using "Examples" instead of "Demo".
In Show HN: AgentGuard – Auto-kill AI agents before they burn through your budget
Honestly feels very vibe-coded [1] [2] and would not really trust my money with something like this. I had to read the code to understand what it actually protects me from, as the README.md (other than telling me it's production-ready, professional, and protects me from so much!) tells me "Supports all major providers: OpenAI, Anthropic, auto-detected from URLs". OpenAI and Anthropic are "all" major providers [3]? [1] https://github.com/dipampaul17/AgentGuard/blob/51395c36809aa... [2] https://github.com/dipampaul17/AgentGuard/commit/d49b361d7f3... [3] https://github.com/dipampaul17/AgentGuard/blob/083ae9896459b...
In Show HN: AgentGuard – Auto-kill AI agents before they burn through your budget

Show HN: AgentGuard – Auto-kill AI agents before they burn through your budget

Your AI agent hits an infinite loop and racks up $2000 in API charges overnight. This happens weekly to AI developers. AgentGuard monitors API calls in real-time and automatically kills your process when it hits your budget limit. How it works: Add 2 lines to any AI project: const agentGuard = require('agent-guard'); await agentGuard.init({ limit: 50 }); // $50 budget // Your existing code runs unchanged const response = await openai.chat.completions.create({...}); // AgentGuard tracks costs automatically When your code hits $50 in API costs, AgentGuard stops execution and shows you exactly what happened. Why I built this: I got tired of seeing "I accidentally spent $500 on OpenAI" posts. Existing tools like tokencost help you measure costs after the fact, but nothing prevents runaway spending in real-time. AgentGuard is essen
Read the rest
tially a circuit breaker for AI API costs. It's saved me from several costly bugs during development. Limitations: Only works with OpenAI and Anthropic APIs currently. Cost calculations are estimates based on documented pricing. Source: https://github.com/dipampaul17/AgentGuard Install: npm i agent-guard
47 points · Open discussion

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