Developer Tools / AI Safety / LLM Guardrails
A Python filter layer for LLM apps that evaluates responses against a Lean-verified Scherf logic backend and can pass, flag, correct, or block output.
The page clearly describes an AI-adjacent developer tool with a concrete purpose: filtering LLM output using a verified logic layer. The README shows installation, a quick-start example, the available actions, and how the checker works, which is enough evidence for a useful public listing. It also has a distinctive angle—formal verification plus claim extraction for safety and user-objectification concerns—that makes it stand out from generic moderation tools.
The crawl gives a strong overview, but it still leaves some practical details unclear: how well the claim-extraction step works in real usage, what kinds of models or runtimes it supports beyond the shown Python API, and how developers would configure or extend the policy in a real application.
Last evaluated 101 days ago. Current rank #1422. Down 2 spots in the rankings.
CodeGraph is a local code knowledge graph for AI coding agents like Claude Code, Cursor, Codex, OpenCode, and Hermes Agent. It aims to cut token use, tool calls, and runtime by letting agents query pre-indexed code structure instead of scanning files repeatedly.
Mercemur is a store automation platform with three interfaces: a REST API, an MCP server for AI agents, and a CLI for editing storefronts as files. The docs show authentication, scopes, rate limits, error handling, pagination, idempotency, and a large API surface for catalogue, orders, customers, pricing, and money.
A zero-dependency C++23 CLI and MCP server that gives coding agents a ranked map of a repository, including call context, blast radius, and tests to run.
Traccia is an AI agent observability and governance platform with OpenTelemetry-native tracing, runtime policy enforcement, prompt registry, evals, cost attribution, and compliance evidence export.
