Releases·Tool Release
Show HN: Sensez – helping coding agents catch their own code smells
A developer released Sensez on GitHub, a tool designed to help coding agents detect code smells like dict[str, Any], boolean flag proliferation, and untestable nested functions that AGENTS.md instructions fail to prevent.
1 engagement1 sourceWed, Sep 2, 2026, 02:29 PM
AI Overview
- sensez is an open-source static-analysis toolkit for Python and JS/TS whose noze module flags duplication, dead code, cycles, and code smells
- Scans run locally in 160–270 ms, fast enough to run on every agent turn while context is still fresh
- In an A/B eval over ~90 tasks with deepseek-v4-flash, sensez cut new structural clones from 129 to 0 and code smells from 14 to 2 at ~9% more token usage
- sensez runs alongside ruff, ESLint, and ty rather than replacing them; planned work includes incremental analysis, a VS Code extension, and semantic duplication detection
Related
Products·launched
Sloppy - open-source PHP code-quality tool that catches AI agent coding mistakes during development
Sloppy is an open-source PHP code-quality tool that detects patterns of AI-generated technical debt, such as silently swallowing exceptions, placeholder code, and tests faked with assertTrue(true). It aims to flag these issues while an AI coding agent is still writing code, rather than after review. It targets developers using AI coding assistants on PHP projects.
Sloppy is an open-source PHP code-quality tool that detects patterns of AI-generated technical debt, such as silently swallowing exceptions, placeholder code, and tests faked with assertTrue(true). It aims to flag these issues while an AI coding agent is still writing code, rather than after review. It targets developers using AI coding assistants on PHP projects.
12 engagement1 sourceredditSun, Oct 4, 2026, 10:16 AM
Products·launched
Benzi: agentic coding harness that reads less source code for better code
Benzi is an agentic coding harness that reduces the amount of source code read by AI agents, aiming to improve code quality and reduce token usage. It addresses the problem of context drift and high token counts in current AI coding agents by using a novel approach to code understanding. It is for developers using AI coding assistants.
Benzi is an agentic coding harness that reduces the amount of source code read by AI agents, aiming to improve code quality and reduce token usage. It addresses the problem of context drift and high token counts in current AI coding agents by using a novel approach to code understanding. It is for developers using AI coding assistants.
2 engagement2 sourcesredditThu, Aug 27, 2026, 07:26 PM
Releases·Tool Release
Show HN: Deslop – Oxlint rules that flag unsafe types, duplicate code, and low-value tests in AI-generated TypeScript
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.
39 engagement1 sourcehackernewsTue, Oct 13, 2026, 05:52 PM
Releases·Tool Release
Dev ships cogext-scan, a zero-dependency CLI that AST-scans LangChain and CrewAI code for silent failures and runaway loops
A developer open-sourced cogext-scan, a zero-dependency Python CLI that uses static AST parsing to flag failure modes in agent code before deployment. It was motivated by production incidents where agents reported success despite failing tools, such as a SendGrid wrapper returning "Email sent" on a 401 Unauthorized. The tool runs offline, requires no account, and outputs an Agent Safety Index score.
A developer open-sourced cogext-scan, a zero-dependency Python CLI that uses static AST parsing to flag failure modes in agent code before deployment. It was motivated by production incidents where agents reported success despite failing tools, such as a SendGrid wrapper returning "Email sent" on a 401 Unauthorized. The tool runs offline, requires no account, and outputs an Agent Safety Index score.
1 engagement1 sourceredditWed, Sep 30, 2026, 12:11 PM
Products·launched
Ironcode: quality-control skill for AI coding agents
Ironcode is a skill for AI coding agents that enforces basic code quality checks, such as disposing streams, avoiding database queries in loops, and validating security-sensitive inputs. It addresses the problem of AI agents producing plausible but flawed code by adding automated checks before completion.
Ironcode is a skill for AI coding agents that enforces basic code quality checks, such as disposing streams, avoiding database queries in loops, and validating security-sensitive inputs. It addresses the problem of AI agents producing plausible but flawed code by adding automated checks before completion.
2 engagement1 sourceredditTue, Aug 4, 2026, 12:01 PM