SuperCompress vs Caveman

Side by side

	Caveman	SuperCompress
What it optimizes	Replies and input context in v4; skill-only mode changes replies	Input context (tool output, logs, files, MCP results, RAG)
How it decides	Local feature bundle; terse reply style in skill-only mode	Query-aware extraction of original lines
Where it runs	Local CLI/proxy; standalone skill also available	Hosted API, plus an MCP tool and hooks for coding agents
Setup	npx @caveman-ai/cli@latest, or install the skill alone	npm install -g supercompress-proxy && supercompress setup
Licence	Open source	Hosted service

Caveman

A. Caveman

Choose the full package for local input compression and terse replies, or the standalone skill for a style change.

Caveman v4 combines a terse-output skill with local input compression, model/effort selection and other agent features. The repository documents per-feature controls. Older tests of the reply skill do not measure the whole current package.

• How it works: Local feature bundle; terse reply style in skill-only mode
• Runs: Local CLI/proxy; standalone skill also available
• Setup: npx @caveman-ai/cli@latest, or install the skill alone
• Licence: Open source

Strengths:

• Near zero setup and footprint
• Works across many agents
• Easy to try and remove

Limitations:

• The standalone skill and the full v4 package have different scope; evaluate the enabled features
• Reply style is a preference; inspect the feature switches if you want input compression without a style change
• Its input compression can overlap with another compressor; test one layer before stacking them

SuperCompress

B. SuperCompress (our product)

Best if your agent keeps pulling big tool results, logs or retrieved docs and only a few lines matter for the question at hand, and you want those lines kept verbatim.

Hosted, query-aware context compression. Your agent or app sends a bulky block (tool output, a log, a diff, a file read, an MCP result, retrieved docs) with the current question, and the hosted Neural Keep model keeps the original lines that answer it, word for word, and drops the rest.

• How it works: Query-aware extraction of original lines
• Runs: Hosted API, plus an MCP tool and hooks for coding agents
• Setup: npm install -g supercompress-proxy && supercompress setup
• Licence: Hosted service

Strengths:

• Keeps original lines verbatim, so error messages, paths, IDs and code survive exactly
• Query-aware: what is kept depends on the current question, not only on the content type
• One setup command wires an MCP tool into each detected coding agent (Claude Code, Cursor, Codex, Windsurf, Cline, Gemini CLI, OpenCode and more), plus hooks where supported
• HTTP API returns original_tokens and kept_tokens so you can measure on your own traffic
• Works with any model provider because the output is plain text

Limitations:

• Hosted: the context you compress is sent to the SuperCompress API
• Compresses input only; it does not change how verbose model replies are
• Not a code index or retrieval system; it shrinks what is already being sent

How to test any of these fairly

Every tool here, including ours, publishes its own numbers. Fewer tokens do not always mean a smaller bill once prompt caching, retries and extra agent turns are counted. Run the same tasks with and without a tool, check the tasks still succeed, and compare cost per finished task on your provider bill.

Disclosure: SuperCompress publishes this page and is listed first because it is ours. Every claim about other tools comes from their own docs or repositories as of 2026-10-31; tell us if anything is out of date and we will fix it.

See also: Caveman alternatives, all comparisons.

FAQ

Is SuperCompress better than Caveman?

The full packages overlap on input compression, but differ in deployment and feature scope. Choose the full package for local input compression and terse replies, or the standalone skill for a style change. Best if your agent keeps pulling big tool results, logs or retrieved docs and only a few lines matter for the question at hand, and you want those lines kept verbatim.

What is the main difference between SuperCompress and Caveman?

Caveman v4 runs a local feature bundle that includes input compression and terse replies. SuperCompress offers hosted query-aware input extraction. The standalone Caveman skill addresses reply style only.

Can I use both?

Usually, if they act on different tokens. Measure cost per finished task with each on and off.

Get API key Coding agents guide All comparisons