# Jev-Checkpoint

> Jev-Checkpoint — ashishakkumar-jev-checkpoint. Use this tool when you need to confidence-gate AI decision-making and ensure accurate next steps. Jev-Checkpoint solves uncertainty problems by routing decisions to proceed, deeper review, or human input, providing a safe and reliable interface for AI agents. It takes in uncertain AI decisions as input and outputs a confidence-gated next step, ideal for use cases requiring high accuracy and reliability.

Canonical page: https://skillsregistry.net/skills/ashishakkumar-jev-checkpoint  
JSON: https://api.skillsregistry.net/v1/skills/ashishakkumar-jev-checkpoint

## Description

A local MCP server that uses TypeSafe Jev to confidence-gate an AI agent’s next step, routing uncertain decisions to proceed, deeper review, or human input.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/ashishakkumar/Jev-Checkpoint)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "ashishakkumar-jev-checkpoint"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ashishakkumar-jev-checkpoint` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ashishakkumar-jev-checkpoint/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt