Claude Code plugin: a 3-cent bouncer for your agent's shell. Jev typed probabilities auto-allow routine commands, deny destructive ones, and flag prompt injection in tool results.
Jev ecosystem projects — page 88
5191 repositories with documented relationships and source evidence.
Give any MCP-capable LLM harness an on-demand real-browser search tool (TypeSafe Jev) with per-run timing and cost tracking.
CI example using Jev to classify failed PR checks and return structured decisions with probabilities.
No project description available.
Local, contract-compatible System One decision server (typed questions -> calibrated probabilities, zero generation). Independent reimplementation; not affiliated with TypeSafe.
Context compaction and safety gating for AI agents via TypeSafe Jev: keeps messages verbatim, no summarization. OpenAI, Anthropic, LangChain, CLI, MCP.
Jev learns your repo's decision norms, then adversarially judges past decisions against them. Unix-style primitives (seed, expand, judge, verify, report, norms) with per-node typed judgments from typesafe-ai/jev.
Real-time hawk-or-dove analysis of Fed press conferences with TypeSafe's Jev vs chat models. Live at fedspeech.pages.dev
Recursive FOLIO document classification with TypeSafe Jev
TypeSafe Jev 1.13 vs Claude Fable 5.1, GPT-6 Astra, Kimi K3, MiniMax M3 and DeepSeek V4.1 Flash on 200 typed decisions: accuracy, calibration, agreement with 100 human annotators, latency and cost
TypeSafe Jev arcade
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TypeSafe.ai Jev Go SDK
A safety boundary for AI-assisted Home Assistant decisions, with explicit policy checks and deterministic state verification.
MCP server exposing TypeSafe's Jev as a judge tool: typed judgments with calibrated probabilities, for any MCP client.
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Hands-on research lab for TypeSafe's Jev (System One model): reproducible benchmarks of Noul/Choice/Score primitives, confidence gating, fan-out latency, agent control — plus a living audit of the Jev ecosystem.
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A hands-on lab for Jev, TypeSafe's System One model — AI decision trees, guardrails and routing with typed answers instead of text
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Never confidently wrong: a TLA+-verified consensus kernel around TypeSafe's Jev, run through 1,680 chaos-tested pharmacy decisions with zero wrong verdicts. Film, code, and every captured call.
Give your Jev language, i'm not finish now
Jev decides whether a batch of logs is worth acting on. Typed questions, confidence gates, nothing executed.
AI defect code suggestions for Non-Conformance Reports, powered by TypeSafe AI's Jev model
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A vocabulary-driven TypeScript runtime for safe, stateful applications powered by TypeSafe AI Jev.
Does ORDER BY over a Jev probability put rows in a defensible order? Independent ranking, calibration and invariant measurements of TypeSafe AI's Jev: passes six pre-registered gates on 360 labeled rows, fails four of six on graded product relevance.
Evidence-gated registry of Jev question packs — curated questions, golden cases and measured evidence for Jev-compatible decision endpoints
Chrome extension that asks Jev whether the page you are on is selling something or reporting first-hand experience, and marks Google results with verdicts it already has or snippet-only estimates, leaving low-confidence ones undecided.