About This Site
AI token optimization stack for reducing agent costs and context Caveman is an AI efficiency operating stack that reduces the cost and context size of agent-native development. It provides an MIT-licensed skill, a free local proxy, an Agent SDK, and planned cloud and enterprise services. Caveman compresses logs, JSON, code, diffs, tables, tool outputs, and files before provider calls while preserving recoverable original bytes. It also supports caching, eval-gated model routing, token usage visibility, savings estimates, and verification workflows. The local wrap works with users' own provider keys and does not require a Caveman account.
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Key Features AI
Core Features
Recoverable compression for logs, JSON, code, files, tool outputs, and other agent context
Token usage visibility with inferred, replayed, and provider-verified savings tracking
Eval-gated caching, model routing, automatic rollback, and byte-safe optimization
Advantages
Free local wrap for one seat with no account required
MIT-licensed skill and open-source ecosystem
Supports more than 30 agents and common developer workflows
Original bytes remain recoverable after compression
Provides detailed token usage and cost visibility
Uses evaluation gates, shadow testing, and rollback to reduce optimization risk
Supports BYOK and states that wrap telemetry contains token counts rather than prompts
缺点：Hosted cloud, verified ledger, and receipt verification are still in design-partner preview
缺点：Local compression and routing savings remain inferred rather than fully provider-verified
缺点：Automatic receipt signing and gainshare charging are disabled
缺点：Paid plans are currently waitlist-based
缺点：Some features, including cloud and enterprise capabilities, are still in development
缺点：Optimization quality may depend on traffic type, provider support, and evaluation coverage
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30-Day Click Trend
08-22
09-05
09-20
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