knowledge-cutoff

Tell your coding agent which dependencies changed after its training cutoff. Diffs types and changelogs, writes a short block into AGENTS.md / CLAUDE.md.

Find which APIs of your pinned Python dependencies changed after your coding model's training cutoff, and give the agent short AGENTS.md / CLAUDE.md notes from a static API diff. No model calls, no API key. CLI, MCP server, Claude Code plugin, GitHub Action.

Claude has never seen 68% of the Claude Code docs: research, interactive charts and a plugin that tells it what it missed. Plus a field guide to Claude and AI tools that says when each page was last checked, in 12 languages.

LLM knowledge cutoff compensator for AI coding agents — corrects outdated versions, deprecated APIs, renamed packages, and removed CLI commands

Benchmarking the true internal knowledge cutoff dates and factual decay of Large Language Models (LLMs) using notable death records.

Daily-updated dataset of what happened after your LLM's knowledge cutoff — news, new places, products and prices. Mostly Korea. JSON, CC BY 4.0.

A structured multi-domain JSON ledger designed to patch knowledge gaps in open LLMs, providing an agent-ingestible context dataset of verified global metrics, policy shifts, and breakthroughs.

Pre-registered head-to-head benchmark of coding-agent context for post-cutoff library changes: Claude Code alone vs Context7 docs vs since-cutoff notes vs both (360 sessions, hidden tests, all transcripts).

API time machine for Python libraries: tells coding agents what changed, in which release, and what to use instead. Local-first MCP server.