01What it is
Sipcode keeps Claude Code’s context clean. It is an open-source toolkit that measures how much of an AI coding agent’s context is bloat, then removes the parts the agent does not need, before they cost you tokens.
02The problem
When the context window fills up with stale, repeated or off-topic output, the answers get worse and every turn costs more, and you cannot tell what is bloat and what is signal.
03How it works
A live hook sits in front of Claude Code’s tools. It trims verbose tool output and drops repeat reads of files the agent has already seen in the same session. Code is read AST-aware through tree-sitter, the project summary it injects can be hard-capped at 2,000 tokens, and sipcode drift shows how much of a session was waste. It also runs as an MCP server with 16 tools. It makes zero network calls: a test fails the build if network code is ever imported.
04The proof
A 62.6% median saving on a locked 20-task corpus that anyone can rerun with sipcode benchmark. The corpus is synthetic, scripted pairs of Claude Code transcripts rather than recordings of live sessions, so it models what the mechanisms remove; sipcode impact measures your own sessions. 2,222 tests pass.
05Where it is now
Live and open source at v1.7.3, with more than 10,000 npm downloads, a listing on the official MCP Registry and #12 Product of the Day on Product Hunt. It also reads OpenAI Codex session logs for spend analytics, and ships a companion, Sipcode Score: a GitHub Action that grades how agent-friendly a repository is on every pull request.