# reactor

> reactor — keugenek-reactor. Use this tool when you need to predict the performance of a LinkedIn post before publishing, to optimize engagement and avoid potential backlash. It provides a verdict (GO/WAIT/IMPROVE/NO) along with metrics such as impressions, debate score, and cringe detection to inform your decision. Ideal for social media managers and content creators seeking to refine their online presence and minimize risks.

Canonical page: https://skillsregistry.net/skills/keugenek-reactor  
JSON: https://api.skillsregistry.net/v1/skills/keugenek-reactor

## Description

Predict LinkedIn post performance before you publish. GO/WAIT/IMPROVE/NO verdict, impressions, debate score, cringe detection. CLI + MCP + AI Skill. Zero LLM calls.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-06-18

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/keugenek/reactor)

## 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": "keugenek-reactor"
    }
  }
}
```

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