AI Agent Tooling (Tokens & Context)
Open-source skills that make AI coding agents cheaper and smarter — token compression, codebase knowledge graphs, and on-device agent runtimes.
alternativas (4)
★ graphify
Ideal para: Codebase as a knowledge graph
Turns any folder of code, schemas, docs, papers, images, or video into a queryable knowledge graph for AI coding assistants.
- +Queryable graph of your code
- +Cuts tokens & tool calls
- +Works with many agents
- −Index step to maintain
codegraph
Ideal para: Local code graph for agents
Pre-indexed, 100% local code knowledge graph across 20+ languages — fewer tokens, fewer tool calls for agents.
- +Fully local
- +Auto-configures many agents
- +Fast incremental parsing
- −Per-repo indexing
caveman
Ideal para: Cutting agent token costs
A Claude Code skill that cuts ~65% of output tokens by making the agent "talk like caveman" while keeping technical accuracy.
- +Big token savings
- +Keeps code/terms exact
- +One-command toggle
- −Terse output style
rtk
Ideal para: Optimizing agent workflows
A toolkit of utilities to optimize "vibecoding" with AI agents — reducing tokens and tightening agent workflows.
- +Agent-workflow utilities
- +Token-aware
- −Younger project
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Want your AI coding agent to use fewer tokens and understand your codebase better? These open-source tools help: knowledge-graph indexers (graphify, codegraph) give agents a queryable map of your code, caveman compresses output tokens, and rtk optimizes agent workflows.