# dsct

> dsct — higebu-dsct. Use this tool when you need to dissect and analyze large packet captures, especially with large language models (LLMs). It solves problems related to inspecting and understanding complex network traffic, providing a command-line interface (CLI) for efficient packet analysis. The tool accepts packet capture files as input and outputs detailed dissection results, making it ideal for use cases involving network troubleshooting and protocol analysis.

Canonical page: https://skillsregistry.net/skills/higebu-dsct  
JSON: https://api.skillsregistry.net/v1/skills/higebu-dsct

## Description

Packet dissector CLI for LLMs and large captures

## Trust

- **Trust score (0–1):** 0.74
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-26

## Source

- **Source listing:** [GitHub](https://github.com/higebu/dsct)

## 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": "higebu-dsct"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/higebu-dsct` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/higebu-dsct/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