verification

Local-first coding agent that runs on the user’s machine and can work across the browser, desktop, terminal, and editor surfaces. The repo says it verifies fixes by reproducing failures and re-running assertions, with install instructions for Windows, macOS, and Linux.

A Python package and CLI for checking how closely an AI-generated answer reuses its source text, with support for verbatim matching, subsequence matching, quotation verification, and pipeline gating.

A verification browser for AI coding agents built on WebKitGTK, aimed at fast visual checks, page assertions, and human handoff. The repository shows install steps, CLI usage, MCP support, and a concrete agent workflow.

A Go/Python tool for verifying AI audit logs, checking chain integrity, tamper detection, and whether a log is independently anchored outside the producing system.

A research report on the current MCP ecosystem, with live crawl numbers, verification rates, category breakdowns, and examples of both strong and weak MCP-positive sites.

A GitHub repository that turns untrusted source material into compact AI skills using evidence gates, validation steps, and audit output.

Cinchor provides tamper-evident accountability records for AI agent actions, letting users verify a real decision against an on-chain record and test whether any field has been altered.

An open-source enforcement layer for AI coding agents that adds frozen specs, tamper-detected tests, independent verification, and hard-blocking gates so unverified work cannot pass.

An early-access AI research assistant that presents a cited mindmap of AI agent safety and alignment research, with expandable nodes, source-backed claims, and built-in verification checks.

Marker is an AI testing and verification platform for voice agents, with a focus on simulation, transcripts, judgments, and versioned evidence across the workflow.

A research page and preprint about using code as the runtime layer for agent systems, with a taxonomy of harness interfaces, harness mechanisms, and scaling patterns for multi-agent workflows.