OpenClaw + decision models
The OpenClaw personal agent. Integrations guard against leaks and decide when triggers should fire.
13 public projects
Local long-term memory for coding agents with an optional Jev reranker that orders recalled memories.
ProjectproductionTypeScriptKorean course code for attaching Jev to Claude Code, Codex and OpenClaw: skills, hooks, routers and open-model comparisons.
ProjectproductionJavaScriptOpenClaw plugin adding a jev_route tool that classifies tasks with Jev and applies routing policy as code, with optional automatic routing.
ProjectbetaTypeScriptBash-native CLI that filters any stream by meaning with Jev, like grep for semantics, so an agent wakes only for lines that matter.
ProjectbetaTypeScriptOpenClaw context engine that asks Jev which tool calls and results are still needed and drops the rest verbatim, never summarising.
ProjectbetaTypeScriptOpenClaw plugin that checks each outgoing agent message against its destination and blocks client names, credentials or internal hosts.
PluginbetaTypeScriptOpenClaw plugin where Jev decides whether a group-chat bot should reply and, optionally, which model tier should answer.
PluginbetaTypeScriptOpenClaw plugin and CLI that turn a plain-language condition into a scheduled trigger, waking the model only when Jev says it is true.
PluginbetaTypeScriptIndependent OpenClaw plugin exposing one explicitly invoked typesafe_decide tool that sends supplied state and typed questions to Jev.
HookbetaTypeScriptCost-, cache- and quota-aware LLM router that classifies each turn with a Jev-class model, prices every route, and checks cheap answers.
ProjectprototypePythonAgent skill and CLI that chains Jev question design: find decision calls, check fit, draft, lint, calibrate thresholds and plan a cascade.
Agent skillprototypePythonZilliz's cross-agent Markdown memory with an optional Jev reranker that asks yes/no relevance questions about retrieved chunks.
LibraryproductionPythonProduction control plane for OpenClaw agents: Jev routes each Slack message to its task, with Temporal workflows, an evaluator and memory.
LibraryproductionPython