Agent Skill and Python workflow for Clay lead scoring, B2B prospect qualification, and people-search ranking with TypeSafe JEV.
Jev ecosystem projects — page 78
5191 repositories with documented relationships and source evidence.
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Thin clojure wrapper for Jev, TypeSafe AI's classification model
TypeSafe Jev
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⚡ DataJev LLM → Analyze Jev → Continue / Switch / Verify / Stop System-1 control for System-2 data agents
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One client for every decision model: Choice, Score and Noul over Jev, OpenRouter, laya, MLX, CrossEncoders and LLM fallback
Compile documents, code, SOPs, and resolved cases into evidence-backed JEV judgments, legal actions, guarded adapters, and measured decision systems.
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Personal LinkedIn feed labels and ad dimming powered by TypeSafe JEV. Bring your own API key. MIT licensed.
App de escritorio y CLI que puntúa la idoneidad de ofertas de empleo con tu perfil, con análisis y mapa de calor. Electron + Jev.
No project description available.
Microsoft.Extensions.AI provider SDKs: Anthropic Claude and TypeSafe AI Jev
Classify your GitHub stars into GitHub Lists with TypeSafe Jev, and review stars worth dropping
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Go client for the TypeSafe System One (Jev) API
Vietnam - Content safety guardrails for AI chatbots: input, output and conversation checks over one policy file with Jev
Judgments from TypeSafe Jev that read like Rust control flow: a yes/no is an if, a choice is an exhaustive match, a score is a comparison.
AI-powered decisions for Magento 2: Jev analyzes orders, customers, products, reviews and abandoned carts and writes the answer right in your admin.
Experimental selective context compaction for Hermes Agent using TypeSafe Jev. Native plugin, local archives, bounded scoring and honest evaluation.
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⚡ Browser agent that acts on a hunch: Jev (TypeSafe System One) picks every click in ~150 ms, an LLM is only needed when confidence drops. Zero-dependency Python on top of agent-browser.
Japanese text linter powered by jev (TypeSafe System One)
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JAST is an experimental SAST (static application security testing) desktop app that uses TypeSafe AI's Jev System One model.
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Apply natural-language codebooks to tables: a CLI and Python API with resumable annotation, exports, and label evaluation.
Context-aware routing for Codex: classify prompts, choose agent profiles, coordinate subagents, and verify results.
把决策模型 Jev 接进亚马逊广告优化的参考实现：规则层出可追溯结论，Jev 出独立第二意见，分歧即信号。输出可落到飞书多维表格。
Typed-judgment model (TypeSafe Jev) driving task-level decisions on a simulated xArm7: reliability measurements, failure map, sensor-freshness gate
A zero-dependency MCP server for TypeSafe's Jev — calibrated, typed judgments for Claude Code, with a local answer cache and cost tracking.