Connect to x.ruv.io, read federation channels and claims, or coordinate authorized work across Ruflo hosts with explicit identity and publishing boundaries.
中文简介正在准备中。当前显示原文说明。
Generate or evolve a repository-specific CLI, MCP and skills harness using MetaHarness, with bounded evaluation and explicit release authority.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Read MetaHarness's current guide and the target repository's instructions. MetaHarness generates a candidate harness; this entrypoint does not implement or certify Darwin, model learning, or sandbox enforcement.
Use ruvnet_plan if available for a deterministic advisory scaffold. Otherwise follow this bounded flow:
--help. Upstream currently documents npx metaharness score <repo> for read-only suitability scoring, and npx metaharness my-bot --template vertical:coding --host claude-code for a coding starter. Pin a reviewed version before repeatable execution. Never interpolate an untrusted goal into a shell command.For an authorized ruOS user-journey evaluation, read Dream Machine's reviewed ruOS runbook. Select a dedicated owned desktop from live status rather than a personal or shared session. Freeze exact revisions, evaluator, workload, environment, nonce, tenant, assertions and thresholds before execution. Require authoritative status: ok, numeric exit code zero, completionVersion: 1, completionVerified: true, and actual screenshot bytes. Missing evidence is INCONCLUSIVE; stdout, screenshot dimensions, hashes, readiness or an ACCEPT receipt cannot grant merge or deployment authority. Keep private screenshots and credentials out of reports.
Scope reusable memory to the repo and principal. Store validated patterns with provenance; retrieve before repeating an expensive experiment. Do not retain secrets or treat previous outcomes as proof for a new environment.
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Connect to x.ruv.io, read federation channels and claims, or coordinate authorized work across Ruflo hosts with explicit identity and publishing boundaries.
中文简介正在准备中。当前显示原文说明。
Choose and validate RuVector or AgentDB memory for an agent application, including provenance, isolation, retention and workload-specific retrieval benchmarks.
中文简介正在准备中。当前显示原文说明。
Discover and integrate RuV Stack projects when the user asks where to begin with ruvnet, which RuV tools fit a goal, or how the stack fits together.
中文简介正在准备中。当前显示原文说明。