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04:43
2026-08-30
dev.to
ai-safety

Your MCP Server Says It Is Read-Only. Who Checked?

A developer built Airlock, an open-source tool that audits MCP servers by comparing their declared tool annotations, such as readOnlyHint, with observed behavior. In tests, Airlock detected all five p…

04:30
2026-08-30
dev.to
ai-agents

An agent trajectory dataset needs more than final answers

A developer detailed best practices for building agent trajectory datasets, emphasizing the need to preserve the full behavioral context—tasks, observations, tool calls, and corrections—rather than on…

03:40
2026-08-30
dev.to
large-language-models

Your LLM cannot compute a birth chart (and it won't tell you)

A developer behind the saju reading service ioreum.com warns that large language models cannot accurately compute Korean saju (Four Pillars) birth charts, as the calculations involve exact calendar ar…

03:38
2026-08-30
dev.to
developer-tools

rulereceipt

A developer is building RuleReceipt, a tool designed to manage rules and configurations across AI coding assistants such as Claude, Copilot, and Cursor, eliminating the need for duplicate setup. The p…

03:05
2026-08-30
dev.to
artificial-intelligence

Why the AI character would not calm down, and how I fixed it

An early version of Say It Ahead had a problem where AI characters would not calm down even when users handled conversations well. The developer fixed it by giving each scenario a model of how a diffi…

03:02
2026-08-30
dev.to
developer-tools

An Open Task Is Not Yet a Contribution

WebAZ has introduced a public contribution interface that lets humans and AI agents discover bounded tasks, inspect their boundaries, and submit structured suggestions before committing to code access…

02:54
2026-08-30
dev.to
developer-tools

How to Update MCP Tools When the Underlying API Changes

A developer detailed a process for updating Model Context Protocol (MCP) tools when underlying APIs change, emphasizing the need to treat MCP tools as contracts with AI clients. The guide covers scann…

02:31
2026-08-30
dev.to
artificial-intelligence

Five bugs in my LLM app that never threw an error

A developer spent two and a half weeks building an AI agent that reads code review history and distills conventions, but encountered five silent bugs that never threw errors. The bugs included Python'…

02:30
2026-08-30
dev.to
large-language-models

LLM Observability: Tracing, Logging, Debugging Agent Runs

A developer details how LLM observability—tracing, logging, and evals—is critical for debugging agent runs, citing a logistics customer-support agent that hallucinated tracking numbers for three weeks…

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