An independent developer launched AI Guard on Product Hunt, an MIT-licensed open-source ESLint plugin with 18 deterministic rules targeting error patterns AI coding assistants introduce in JS/TS. It ships as a CLI, a GitHub Action with SARIF output, and an init-context command that generates CLAUDE.md/.cursorrules files. Launch feedback is already reshaping the roadmap toward measuring whether instruction files actually change agent behavior.
The maintainer of AI Guard, an open-source ESLint plugin for AI-assisted JS/TS, posted a follow-up acknowledging a flaw in its planned benchmark. A commenter, Deep_Ad1959, pointed out the linter fires at CI time stamped with the commit, not the agent turn that wrote the code, so it can't directly measure whether init-context reduces agent violations. The team is redesigning the measurement around post-tool-use hooks.
The maintainer of AI Guard, an open-source ESLint plugin for AI-assisted JS/TS, posted a follow-up acknowledging a flaw in its planned benchmark. A commenter, Deep_Ad1959, pointed out the linter fires at CI time stamped with the commit, not the agent turn that wrote the code, so it can't directly measure whether init-context reduces agent violations. The team is redesigning the measurement around post-tool-use hooks.
AI Guard is a set of 18 ESLint rules for JavaScript/TypeScript that detect recurring code-quality mistakes AI coding assistants make, such as floating promises, empty catch blocks, hardcoded secrets, and SQL string concatenation. It targets developers who use tools like Claude Code, Cursor, and Copilot and want to stop these patterns from reaching commits. LLMs are the source of the problematic patterns being caught, not part of the tool itself.
AI Guard is a set of 18 ESLint rules for JavaScript/TypeScript that detect recurring code-quality mistakes AI coding assistants make, such as floating promises, empty catch blocks, hardcoded secrets, and SQL string concatenation. It targets developers who use tools like Claude Code, Cursor, and Copilot and want to stop these patterns from reaching commits. LLMs are the source of the problematic patterns being caught, not part of the tool itself.
A developer launched Deslop on GitHub via Show HN, a set of Oxlint rules targeting TypeScript code written by AI. It flags unsafe types, duplicate code, and low-value tests.
A developer launched Deslop on GitHub via Show HN, a set of Oxlint rules targeting TypeScript code written by AI. It flags unsafe types, duplicate code, and low-value tests.
A developer suggests building a tool that runs coding agents on tasks twice—once with CLAUDE.md and once without—to compare token usage, test pass rates, and edit counts. The idea aims to quantify whether the configuration file actually improves agent performance.
A developer suggests building a tool that runs coding agents on tasks twice—once with CLAUDE.md and once without—to compare token usage, test pass rates, and edit counts. The idea aims to quantify whether the configuration file actually improves agent performance.
AI Guard is an ESLint plugin and CLI that acts as a safety net for developers using AI coding assistants like Claude Code, Cursor, and Copilot. It automatically detects common problematic patterns in generated code, such as floating promises, empty catch blocks, placeholder secrets, and missing auth middleware, helping developers avoid committing flawed code.
AI Guard is an ESLint plugin and CLI that acts as a safety net for developers using AI coding assistants like Claude Code, Cursor, and Copilot. It automatically detects common problematic patterns in generated code, such as floating promises, empty catch blocks, placeholder secrets, and missing auth middleware, helping developers avoid committing flawed code.