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Caveman

why use many token when few do trick

Details

External ID
1220849
Source
PH
Company
—
Product
Caveman
Website domain
producthunt.com
Launched
Aug. 13, 2026
Cohort
—
Upvotes
160
Upvotes percentile
0.08146067415730338
Tags
Open Source, Developer Tools, Artificial Intelligence, GitHub
Fetched at
Sept. 7, 2026, 1:23 a.m.
Updated at
Sept. 7, 2026, 1:23 a.m.

Description

One command wraps Claude Code, Codex, Hermes, and more with a local proxy that compresses logs, tool output, and files before every provider call. In a pinned 54-run benchmark: 33.2% fewer input tokens with 18/18 correctness checks. Caveman can also run any existing agent skill with ~70% fewer tokens by loading text as images. Built on an open-source ecosystem with 97K+ GitHub stars.

Enrichment

Theme
Claude integrations and coding agents
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Commercial product
Normalized one-liner
token optimization for llm inference
Manually corrected
False

Could you build this?

Yes It acts as a local HTTP reverse proxy that intercepts outbound LLM requests, applies regex/heuristic token reduction or summarization algorithms to system prompts and tool logs, and forwards them.

Competitors

Other products that read as similar to this one — 139 launches clear the similarity bar, closest 8 shown.

Attention rank: #137 of 140 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 280 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a model & infra tool for Fintech yet.