# tenbin

> tenbin — simota-tenbin. Use this tool when you need to decompose complex judgments into manageable components, such as Choice, Score, and Noul questions, and calibrate thresholds for accurate decision-making. Tenbin solves problems related to judgment decomposition, linting, and threshold calibration, providing outputs in the form of calibrated code. It is ideal for use cases involving data labeling and measurement, particularly when integrating with the TypeSafe AI System One API.

Canonical page: https://skillsregistry.net/skills/simota-tenbin  
JSON: https://api.skillsregistry.net/v1/skills/simota-tenbin

## Description

MCP server and agent skill for the TypeSafe AI System One API (Jev): decompose a judgment into Choice / Score / Noul questions, lint them, measure on labelled data, and put calibrated thresholds in code

## Trust

- **Trust score (0–1):** 0.84
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/simota/tenbin)

## 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": "simota-tenbin"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/simota-tenbin` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/simota-tenbin/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