Skein

Keel is a local-first native macOS coding workspace that runs coding agents through a Rust/GPUI application. It combines sessions, a composer, transcripts, a terminal, change inspection, settings, Git history, crash recovery, and an agent graph showing active agents, subagents, and files as shared context; agents can be steered or stopped from the graph. It connects Claude Code, Codex, Cursor, Grok, Hermes, and pi through the Agent Client Protocol, and also includes an embedded DeepSeek agent loop with host-enforced tool focus. For unpinned tasks, a local Laya selector running through Core ML or an optional hosted Jev selector chooses among host-prepared routes or abstains. Keel validates each choice before applying it, falls back to the ordinary route when a choice is rejected, stale, or expired, and records candidates, validation, fallback, and observed outcome in bounded decision receipts. Decision receipts can be exported as JSONL and summarized with CLI reports. Keel also provides headless and daemon modes, while each coding provider retains its own authentication, model configuration, and tool loop. The repository supports Apple Silicon and macOS 15 or later for the packaged Laya model. It can be built from source, but the repository does not currently publish downloadable app releases; packaged builds are ad hoc signed development builds. Automatic training, public installer distribution, cloud sync, and native Codex realtime voice are not implemented or included in this build.

Reasonix is an open-source AI coding agent built around a local engine and distributed as a self-contained static Go binary. It is designed for DeepSeek, with DeepSeek provided as a preset, while configuration can target OpenAI-compatible endpoints and optionally use separate executor and planner models. The agent can be used through a terminal or desktop app, in a browser, or from an editor through ACP; it provides plan mode, permissions, workspace sandboxing, per-turn checkpoints, and MCP- or extension-based plugins. Its context maintenance is designed around prefix-cache stability, including a stable startup environment summary and pruning of stale tool output before compaction.

Shim is a local-first, terminal-based AI harness for connecting model APIs, MCP servers, and Agent Skills. It runs as a single static binary with no runtime dependencies, desktop UI, daemon, telemetry, or bundled model weights; it is a harness rather than an inference engine. It provides both a scriptable CLI and natural-language control. An optional local model routes management requests to an allowlisted command, while mutating commands such as file edits, shell commands, and MCP calls require confirmation by default. Shim supports OpenAI-compatible and Anthropic model adapters, MCP over stdio and Streamable HTTP, and on-demand loading of SKILL.md files from configured skill directories. Configuration is stored as JSON and sessions as append-only JSONL, with credentials supplied through environment variables. The project is written using only the Go standard library and is released under the MIT license.

SKI is a voice-first coding harness for macOS from Pattern AI Labs. It lets users speak to coding agents and hear their responses, while running agents such as Claude Code, Codex, Cursor, OpenCode, Antigravity and pi side by side. Each chat receives its own Git branch and worktree, with live diffs, cross-project status, agent handoffs and voice-triggered pull requests. SKI reconstructs spoken intent using project context, shows the interpretation before sending it to an agent, and requires confirmation for irreversible actions. It can chain agents, such as having one agent plan a task and another implement the plan, and supports routing work among users' existing model and agent accounts. Project code, chats and agent execution remain on the Mac; voice processing uses the cloud and the site says the voice is not stored. The full harness is available for macOS with free and paid plans, while Windows and Linux are listed as forthcoming.

SPIFFE is a framework and set of standards for identifying application services and securing communication between them. SPIRE, the SPIFFE Runtime Environment, is a toolchain of APIs that establishes trust and issues strongly attested, cryptographic identities to workloads across heterogeneous platforms such as virtual machines, cloud environments, and private data centers. These identities support use cases including mutual TLS and JWT authentication, passwordless access to databases and platforms, service-mesh federation, zero-trust service authentication, and bridging Kubernetes with other infrastructure. SPIFFE and SPIRE are Cloud Native Computing Foundation graduate projects.