jev

TypeSafe AI's Jev System One model for typed software decisions: Choice/Score/Noul question primitives, state design, confidence gating, the direct api.typesafe.ai /v1/systemone API, typesafe-sdk (Python) and @typesafe-ai/sdk (JS), Cloudflare Workers AI typesafe/jev (binding, REST, AI Gateway), Vercel AI Gateway/OpenRouter/LiteLLM routes, errors incl. 401-vs-403, limits, pricing, Jev 1.13 weaknesses, prompt-injection risk. WHEN: "jev", "Jev 1.13", "TypeSafe", "typesafe.ai", "typesafe/jev", "System One", "systemone", "system_one", "typesafe-sdk", "@typesafe-ai/sdk", "Noul", "jev-latest". Do NOT use for prompt-injection threat modeling (ai-security), MCP servers (mcp), agent loops (claude-agent-sdk, openai-agents-sdk, google-adk), harness config (claude-code, codex), generic OpenRouter/Bedrock routing (inference-providers), LLM-judge grading (evals), or Lightbend's Typesafe/Scala.

What does this entry provide?

jev is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 38/100. # Jev (TypeSafe AI) Jev is TypeSafe AI's hosted "System One" model. You send it one `state` plus a map of typed questions, and it returns typed answers with cal. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding jev to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: GitHub Skill Search
Quality: 38/100
Install method: codex
Repo: chrishuffman5/domain-expert
Repo updated: Oct 27, 2026

Install command

codex skill install chrishuffman5/domain-expert

Install method: codex

Review the upstream source before running this command.

GitHub project

Quality

Repo stars

Repo updated

Unknown

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.
Documentation (10) and description quality (10): parsed manifest or SKILL.md frontmatter, and a real description rather than a placeholder.

Security signals

highMatched in: skillBody
Recursively force-deletes a root, home, or wildcard path — capable of wiping user data.
rm -rf ~Dispute this flag?

Scan coverage: Install metadata and the indexed document body.

Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.

Discovery note

# Jev (TypeSafe AI) Jev is TypeSafe AI's hosted "System One" model. You send it one `state` plus a map of typed questions, and it returns typed answers with calibrated probabilitie

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