# prediction

> Use this tool when you need to forecast outcomes or trends based on historical data, solving problems such as demand forecasting, risk assessment, or resource allocation. It takes in datasets and model parameters as inputs and outputs predicted values or probabilities, providing insights to inform decision-making. Ideal for use cases where data-driven predictions can drive business or strategic outcomes.

Canonical page: https://skillsregistry.net/skills/zjl13031-byte-prediction  
JSON: https://api.skillsregistry.net/v1/skills/zjl13031-byte-prediction

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/zjl13031-byte/prediction)
- **Repository:** <https://github.com/zjl13031-byte/prediction>

## 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": "zjl13031-byte-prediction"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/zjl13031-byte-prediction` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/zjl13031-byte-prediction/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