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LLM knowledge cutoff compensator for AI coding agents — corrects outdated versions, deprecated APIs, renamed packages, and removed CLI commands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

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.