# decision-table

> decision-table — tetracoralla-decision-table. Use this tool when you need to evaluate complex decisions and constraints in a deterministic manner, solving problems such as ruleset validation and fact evaluation. It provides inputs for rules, facts, and constraints, and outputs evaluated decisions and validation results. Ideal for use cases requiring precise and reliable decision-making, such as policy enforcement and compliance checking.

Canonical page: https://skillsregistry.net/skills/tetracoralla-decision-table  
JSON: https://api.skillsregistry.net/v1/skills/tetracoralla-decision-table

## Description

Provides deterministic decision and constraint evaluation for AI agents. Supports ruleset validation, fact evaluation, and constraint checking via MCP tools.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/rwtzeflzwp)
- **Repository:** <https://github.com/tetracoralla/decision-table>

## 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": "tetracoralla-decision-table"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/tetracoralla-decision-table` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/tetracoralla-decision-table/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