# sigmeta

> sigmeta — cognis-digital-sigmeta. Use this tool when you need to organize and standardize signal metadata, such as frequency, modulation, and bandwidth, to solve problems like data inconsistency and improve signal analysis. It takes in raw signal metadata as input and outputs a normalized catalog, enabling efficient signal classification and comparison. Ideal for use cases involving signal processing, telecommunications, and data analysis, where standardized metadata is crucial for accurate insights.

Canonical page: https://skillsregistry.net/skills/cognis-digital-sigmeta  
JSON: https://api.skillsregistry.net/v1/skills/cognis-digital-sigmeta

## Description

Parse and classify signal metadata (freq, modulation, bandwidth) into a normalized catalog.

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/cognis-digital/sigmeta)

## 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": "cognis-digital-sigmeta"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cognis-digital-sigmeta` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cognis-digital-sigmeta/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
