A tool that makes Claude Code shut up, plus a knowledge graph builder worth trying

The Lens

Caveman strips the fluff from Claude Code responses. Install it with one command, activate with /caveman, and your AI assistant drops the pleasantries, hedging, and filler words while keeping full technical accuracy. Average savings: 65% fewer output tokens. Multiple intensity levels: Lite stays professional but terse, Full drops articles and uses fragments, Ultra goes telegraphic, and Wenyan variants compress into classical Chinese. Code blocks, error messages, git commits, and technical terms pass through untouched. Version 2 added a compression engine that squeezes model input as well: tool outputs, logs, and JSON get compacted before they hit your context window, and a companion tool rewrites your CLAUDE.md and memory files to cut input tokens too. It works across 30+ AI coding agents, not just Claude Code. Cursor, Copilot, Windsurf, Cline, Codex, all supported. Heavy token users will feel the difference in both speed and cost. The catch: it started as a meme but the benchmarks are real, backed by a real 2026 research paper. Ultra mode can be hard to read. And v2 split the licensing: the skill, CLI, and SDKs stay MIT, while the engine, proxy, and platform components moved to BSL-1.1, free to self-host including production, only blocking resale of Caveman as a service. The split is per-component, so the LICENSE file in each package is the authority.

The Lens

Graphify reads your entire codebase, docs, PDFs, and even screenshots, then builds a knowledge graph you can actually navigate. It parses 19 languages via tree-sitter for code and uses an LLM for everything else. The result is an interactive HTML visualization showing how your architecture, concepts, and files connect. The first extraction pass costs real API tokens (Claude or GPT), proportional to your corpus size. After that, incremental updates via SHA256 caching mean re-runs only process changed files. The 71x token compression claim is real for subsequent queries, not the initial scan. Runs as a /graphify slash command inside Claude Code, Codex, or OpenCode. For developers onboarding to large or unfamiliar codebases: this is genuinely useful. Architecture reviews, cross-referencing code with design docs, understanding how a monorepo fits together. Exports to Neo4j, Obsidian vaults, or standalone wikis. The catch: it is a plugin, not a standalone tool. You need Claude Code or a compatible AI assistant as the runtime. Quality of inferred relationships depends on the underlying LLM, and the initial scan of a large repo is not cheap.

The Lens

OpenHarness is agent infrastructure you pip install: the tool-calling loop, 43 built-in tools for files, shell, search, web, and MCP, plus skills, memory, permission modes, and multi-agent coordination. It also ships ohmo, a personal agent built on top of it that lives in Slack, Discord, Telegram, or Feishu and will fork a branch, write code, run tests, and open a PR on its own. MIT, Python 3.10 or newer, free. The ohmo part is the interesting trick. It runs on a Claude Code or Codex subscription you already pay for rather than a separate API key, so a chat-driven coding agent costs nothing extra. Setup is pip install openharness-ai, then oh setup to pick a provider and ohmo gateway start to put it in your chat app. It reads CLAUDE.md, loads Anthropic-style skills and plugins, and compacts its own context. Here is the problem. The last commit landed June 4, 2026, the last PyPI release was 0.1.9 on May 7, and there are dozens of open issues with nobody working them. This is a university research group's project that got popular fast, and popularity is not maintenance. For anything you depend on, langchain-ai/langgraph and crewAIInc/crewAI have real release cadences; for the coding agent job specifically, openclaw/openclaw is still shipping. The catch is that a stalled repo and a permission system make a bad pair. ohmo runs shell commands and opens PRs on your behalf, which is exactly the code you want getting security fixes. Fine for a prototype on a throwaway repo. Not something to point at code you care about until commits resume.

The Lens

RustFS is a MinIO alternative written in Rust. It speaks the S3 API, so any tool that works with AWS S3 works with RustFS. The pitch is performance: Rust's memory safety and efficiency versus MinIO's Go implementation. Self-hosting is free under Apache 2.0. You get S3-compatible API, erasure coding for data durability, distributed mode for spreading storage across nodes, and a web console for management. The catch: this is very new. It's getting a lot of attention, but attention isn't maturity. MinIO has been battle-tested in production for years. RustFS documentation is still developing, and the ecosystem of plugins, integrations, and operational knowledge is thin. If you're storing data you can't afford to lose, this is a risk. If you're experimenting with self-hosted object storage or building a non-critical pipeline, it's worth a look. But for production storage, MinIO is the safer bet today.