Keep Claude Code's context clean for sharper answers
Context hygiene for Claude Code. Caps verbose tool output and dedupes same-session re-reads so the model sees signal, not noise. Anthropic measures 29% quality lift from cleaner context. Proof: 62.6% median tool-output savings on a locked 20-task benchmark. MIT.
Hey PH. I'm Anuj, solo indie dev. Built Sipcode because I kept watching Claude Code re-read the same files 6-8 times per session and re-print 4,000-line npm install logs into its context. Each unnecessary token in the window pushes signal out and makes the next answer worse. That is the reliability problem I built it to fix.
It is a PreToolUse hook for Claude Code. Caps verbose output (git log, npm install, grep, tsc), dedupes same-session re-reads of unchanged files, exposes 15 MCP tools so Claude can read its own context-hygiene stats. Anthropic's own research: cleaner context lifts quality 29% and cuts agent errors 40%. That is the mechanism Sipcode targets.
Tokens saved are the PROOF the context got cleaner. Locked 20-task benchmark: 62.6% median tool-output savings, $67.43 per corpus run, reproducible on any machine. The benchmark task list is checked into the repo.
Honest disclosure that became the launch story: last week my drift tool said 624,940 tokens wasted in a single session. My proxy --stats credited only 7,553 saved. 83x undercount, my own tool lying to me. Root cause was mid-session installs leaving the first half of the session uncached. Shipped v1.6.15 with Verified Warm-Fill 24h later, drift now reads "no drift detected." Shipped v1.6.16 today with cache-defer and grep-cap fixes. Three releases in nine days.
MIT, zero network calls in normal use (privacy test fails the build if anyone imports node:http in src/). Happy to answer anything technical, especially the Warm-Fill correctness proof or the benchmark methodology.
If Sipcode saves you a session, a star on the repo at github.com/Anuj7411/sipcode would mean a lot to a solo project trying to find the people who would actually benefit from this.
About Sipcode on Product Hunt
“Keep Claude Code's context clean for sharper answers”
Sipcode launched on Product Hunt on June 23rd, 2026 and earned 135 upvotes and 30 comments, placing #12 on the daily leaderboard. Context hygiene for Claude Code. Caps verbose tool output and dedupes same-session re-reads so the model sees signal, not noise. Anthropic measures 29% quality lift from cleaner context. Proof: 62.6% median tool-output savings on a locked 20-task benchmark. MIT.
On the analytics side, Sipcode competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Sipcode performed against the three products that launched closest to it on the same day.
Who hunted Sipcode?
Sipcode was hunted by Anuj ojha. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Sipcode including community comment highlights and product details, visit the product overview.
Anuj ojha