今日必看

Show HN: MCPJam - the first testing & evaluations platform for MCP servers

Prathmesh, CEO of MCPJam here. Users now start in ChatGPT, Claude, Cursor, and other AI clients. They reach your product through your MCP server. That means your users often aren’t in your product anymore. You can’t see what they prompted for, how the agent interpreted it, or whe

Why Suddenly higgsfield made its core repo Opensource?

comment down your answer

Updating your Xcode project configuration file format

Secure-Eval-Worker: Least-Privilege JavaScript Execution in Node.js

Show HN: Linting 216 public Claude Code skills – 69% won't reliably trigger

I built a linter for Claude Code artifacts (skills, subagents, slash commands, .mcp.json configs, and plugins) and then pointed it at a pile of public repos to see what people actually ship. A few of the numbers surprised me enough that I wrote them up. The one that stuck: across

When an AI Agent Deletes Your Database

Build Your Own AI Agent Harness in C#

Auto SR Comes to Intel Core Ultra Series-3 Processors

Insurance Agent Benchmark: 166 real-world cases for evaluating insurance AI

Workout by Muscle – Claude Solution

A service marketplace for agents like agent-to-agent Fiverr

Come watch the AI Agents do the work

Use C# unions and closed hierarchies in ASP.NET Core

Show HN: Craigslist for agent skills, curated by a human

hey, i'm nick (@skeptrune on X). i have been using ai for a lot of things i'm not an expert in and thought it would be nice to try and buy paid skills for helping it accomplish those tasks more efficiently. for example, redlining contracts, creating ai generated videos, different

Show HN: Aclif – Agent CLI framework: one grammar, canonical names across SaaS

Simple discovery of the provider's default schemas is possible without any credentials (since they are built into the binary). If you want it to fetch customizations of your specific instance, give it credentials to your org. The repo has more details. https://github.com/agent-cl

A visual large language foundational model for medical image recognition using clinician-contributed online resources

arXiv:2609.06914v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong capabilities across diverse domains, showing considerable potential in medicine. However, their application in medical settings remains limited by the scarcity of visual ques

BENCHCOMPASS: From Scores to Signals for Training and Harness Decisions in Payment-Domain LLMs

arXiv:2609.18270v1 Announce Type: new Abstract: Payment operations are a critical financial infrastructure, but the value of large language models in this domain remains unclear because payment rules change quickly, evidence is fragmented, and decisions depend on transaction stat

Compiled Agency: Frontier General-Purpose Coding Agents Build Winning Game Players from Bare Interaction - from Flappy Bird to StarCraft II and Civilization

arXiv:2609.18996v1 Announce Type: new Abstract: LLM agents have repeatedly struggled to convert knowledge of a game into competent play, even when researchers build the agent around the model - supplying perception, memory, skill libraries, planners, or executable-policy scaffold

EvoUndo: Recoverability-Constrained Self-Evolution for LLM Agent Harnesses

arXiv:2608.28363v2 Announce Type: replace Abstract: LLM agents increasingly modify their own prompts, tools, middleware, resources, and execution harnesses at runtime. Such self-evolution can improve capability, but a successful mutation may leave persistent effects that cannot b

Linguistic Triggers of Gender and Racial Bias in Open-Weight LLMs Applied to Recruitment

arXiv:2609.18106v1 Announce Type: cross Abstract: Open-weight large language models are rapidly entering hiring pipelines, yet their discriminatory failure modes -- and the regulatory exposure these create under the EU AI Act high-risk classification (Annex III) and U.S. EEOC adv

PentestChain: A Cost-Aware, MCP-Orchestrated Framework for Automated Penetration Testing with Free-Tier LLMs

arXiv:2609.18120v1 Announce Type: cross Abstract: AI-driven penetration testing has been demonstrated with premium frontier models such as GPT-4, but the per-engagement token cost makes continuous, automated testing unaffordable for the smaller organisations that need it most. Th

Scaling Articulated Rationales for MLLM-based Recommendation

arXiv:2609.17639v1 Announce Type: cross Abstract: Modern recommendation systems largely infer user preferences from implicit behaviors such as clicks, watch time, and negative feedback, but these signals reveal what users do rather than why they like or dislike content. This work

StableEval Arena: A Cost-Aware Agentic Benchmark for Stablecoin Price Stability Prediction

arXiv:2609.18949v1 Announce Type: cross Abstract: We introduce StableEval Arena, a cost-aware benchmark framework for evaluating agentic AI systems on stablecoin peg-risk prediction. StableEval Arena evaluates LLM-backed agentic systems on diagnosing peg stress and forecasting de

The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?

arXiv:2609.17863v1 Announce Type: new Abstract: LLM inference optimizations report speedups on different models, GPUs, prompts, and quality metrics, making them hard to compare or combine. We build a cost, quality, and latency Pareto atlas to identify the best configurations for