# s2s-forecasting-expert

> s2s-forecasting-expert — manmeet3591-s2s-forecasting-expert. Use this tool when you need to build and deploy AI-based Subseasonal-to-Seasonal (S2S) forecasting systems, solving problems of predicting weather and climate patterns over medium-term horizons. It takes in historical climate data as input and outputs accurate forecasts, enabling informed decision-making in various industries. Ideal for use in environmental monitoring, agriculture, and emergency management contexts where medium-term weather forecasting is crucial.

Canonical page: https://skillsregistry.net/skills/manmeet3591-s2s-forecasting-expert  
JSON: https://api.skillsregistry.net/v1/skills/manmeet3591-s2s-forecasting-expert

## Description

End-to-end builder for AI-based Subseasonal-to-Seasonal (S2S) forecasting systems.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-09-26

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/manmeet3591-s2s-forecasting-expert)

## 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": "manmeet3591-s2s-forecasting-expert"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/manmeet3591-s2s-forecasting-expert` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/manmeet3591-s2s-forecasting-expert/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