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Alternatives
Software like oneharness-cli
What else does this job. Matched on what each project does, not on who links to whom.
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- everyharnesspypi.orgeveryharness is an offline-first command-line and terminal user interface for running locally available machine-learning models through pluggable harnesses. It is intended for developers and ML practitioners who need a flexible local model runner.
- Harness CLIrexai.topHarness CLI is a local workflow layer for AI coding clients including Codex, Claude, Gemini, OpenCode, Hermes, and Grok. It adds project memory, multi-agent collaboration, model routing, workflow governance, and verification without replacing the underlying coding client.
- harness-babypypi.orgHarness Baby is an MIT-licensed command-line tool that bootstraps and scores repository harnesses for coding agents. It is intended for developers who need to configure and evaluate repository-level tooling using static analysis.
- ai-harness-clipypi.orgai-harness-cli is an MIT-licensed command-line tool for installing tool-agnostic agents, skills, commands, hooks, and rules across AI development tools. It is intended for developers managing reusable AI tooling configurations across environments such as Claude Code, Codex, and OpenCode.
- hiclaw-harness-workerpypi.orghiclaw-harness-worker is an open-source CLI tool that delegates agent loops to various AI code models, including Claude Code, Gemini CLI, OpenCode, and Codex. It includes a remote harness CLI for developers automating agent workflows.
- aegis-harnessgithub.comaegis-harness is an open-source CLI tool that orchestrates multiple coding agents, including Claude Code, Gemini CLI, and OpenCode, within a unified full-screen terminal UI. It is designed for developers managing multi-agent coding workflows and supports the MCP protocol.
- horus-harnesspypi.orghorus-harness is an open-source CLI tool that provides a project-centric dashboard for managing and coordinating official coding-agent command-line interfaces. It helps developers maintain continuity and control across multiple agent-based workflows.
- local-agentic-harnesspypi.orglocal-agentic-harness is an open-source, local-first tool for orchestrating autonomous AI agents. It provides both a command-line interface and a graphical user interface, supports bounded tools, and includes deterministic review gates for automation workflows. Designed for developers who want provider-neutral, locally controlled agentic automation.
- harness-scorecardpypi.orgharness-scorecard is an open-source CLI tool that provides linting, A-F maturity grading, and security analysis for coding-agent harnesses such as Claude Code and Codex. It helps developers maintain high code quality and security standards.
- OpenHarnessopen-harness.devOpenHarness is an open-source toolkit designed for building AI agents in code, offering developers composable and stateless primitives to create agent harnesses similar to Claude Code-like products. It provides a TypeScript SDK that enables full control over agent behavior, message history, and state management, allowing users to inspect, modify, or share state between agents as plain arrays. The platform is built on top of the Vercel AI SDK, supporting integration with model providers such as OpenAI, Anthropic, Google, or any compatible provider. Key features of OpenHarness include composable middleware for functionalities like turn tracking, retries, context compaction, and persistence, which can be mixed and matched as needed. Developers can implement subagent hierarchies, delegating tasks to specialized child agents with background execution and Promise-like combinators. The toolkit also supports automatic two-phase context management, which involves pruning old tool results and applying LLM-powered summarization to maintain relevant context for the agents. Tool permissions can be managed through asynchronous approval callbacks, enabling gating of tool execution in various interfaces including CLI prompts, web modals, or external services. OpenHarness also offers integration with the Model Context Protocol (MCP), allowing connection to any MCP server via standard input/output, HTTP, or SSE transport. md files. The SDK is compatible with both web and CLI environments, providing React hooks, Vue composables, and streaming support to build agents for any runtime. js or edge runtimes. OpenHarness is released under the MIT License and developed by MaxGfeller, emphasizing its open-source nature and flexibility for developers seeking to construct advanced, customizable AI agent systems.
- harnessieharnessie.comHarnessie is an open-source framework designed for verifiable orchestration of multi-agent AI workflows, emphasizing user control and auditability. It addresses the risks of unsupervised AI by ensuring that every action taken by an AI model is subject to independent verification and explicit user consent before any side effect occurs, such as changing a file or running a command. No sensitive data leaves the models controlled by the user, and every action—whether by AI or human operator—is recorded in a hash-chained audit log, making tampering detectable. The framework structures jobs using three types of agents: an orchestrator that decomposes tasks, workers that execute tasks in isolated environments, and verifiers that independently check results. Each step in a workflow is separated by checkpoints, and the system defaults to failing closed, meaning no action is completed without explicit approval. When a judgment call is required, the process halts for human intervention, ensuring the final decision remains with the operator. Disagreements between agents are recorded rather than averaged, and declined actions are logged without being overridden. Harnessie is brain-agnostic, allowing users to switch between local, private, or remote AI models—including those accessible via OpenAI-compatible endpoints—by editing a single configuration file. The framework supports eight providers and eleven verified models, and its structure remains consistent regardless of the underlying model. Installation requires Python 3.11+ and PyYAML, and can be performed using pip, pipx, uv, or brew. Model adapters rely on the standard library, with no dependency on vendor-specific SDKs. The tool is self-hostable and released under the Apache-2.0 license. It includes a test suite and evaluation scorecard that can be run against a deterministic mock environment without network access, allowing users to validate its operation before integrating any API keys. Harnessie is suited for developers and operators who need strict control, verifiability, and auditability in multi-agent AI workflows, particularly where sensitive data and independent verification are priorities.
- superharnessgithub.comsuperharness is an open-source CLI framework for managing session handoff between multiple AI coding agents, such as Claude Code and Codex. It is designed for developers and researchers working with autonomous agent systems.
- jharness-toolspypi.orgjharness-tools is an open-source CLI toolkit offering ready-to-use filesystem, shell, and agent interaction utilities for JHarness. It streamlines automation and scripting tasks for developers working with the JHarness framework.
- harnessgympypi.orgharnessgym is an open-source CLI framework for benchmarking, testing, and improving agent harnesses for AI code agents such as Codex. It supports iterative improvement, MCP, and is designed for AI researchers and developers.
- harness-to-mcpgithub.comTurn harness internal tools into a standard MCP server — compatible with Claude Code, Codex, OpenCode, and more.
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