# Ternary Intelligence Stack

> Use this tool when you need to enhance your AI agent's decision-making capabilities with a third state, "hold", to handle ambiguous data and avoid structural errors. The Ternary Intelligence Stack solves problems of binary systems forcing yes/no decisions on uncertain information, providing tools like trit_decide and trit_consensus to facilitate more informed decision-making. It takes in ambiguous data as input and outputs a routing instruction to either proceed, wait, or block, making it ideal for use cases requiring nuanced and evidence-based decision-making.

Canonical page: https://skillsregistry.net/skills/rfi-irfos-ternlang  
JSON: https://api.skillsregistry.net/v1/skills/rfi-irfos-ternlang

## Description

Your AI agent has two states. Ternlang gives it three.                                                 
                                                            
30 tools —  FREE, no key needed.                                                                     
   
The third state isn't null. It isn't "maybe". It's hold (trit=0) — a first-class routing instruction   
that tells your agent: evidence insufficient, gather more before committing. Every binary system that
forces yes/no on ambiguous data is making a structural error. We fixed that.                           
                                                            
  ⚡ trit_decide · trit_consensus · trit_vector · moe_orchestrate · ternlang_run · trit_audit            
  ⚡ MoE-13 deliberation engine · EU AI Act Art.13/14/15 · BET VM (real compiler, not a sim)
                                                                                                         
  affirm = proceed. hold = wait. reject = block.                                                         
                                                                                                         
  Built in Graz, Austria by RFI-IRFOS. v1.0.0

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-07-03

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/rfi-irfos/ternlang)

## 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": "rfi-irfos-ternlang"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/rfi-irfos-ternlang` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/rfi-irfos-ternlang/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