# sendiment

> sendiment — leonwangg1-sendiment. Use this tool when you need to provide AI agents with persistent memory that automatically cleans and updates itself across sessions. It solves problems of knowledge inconsistency and staleness by forgetting outdated information, merging duplicates, and resolving contradictions. Ideal for applications requiring long-term memory and data consistency, such as chatbots and virtual assistants.

Canonical page: https://skillsregistry.net/skills/leonwangg1-sendiment  
JSON: https://api.skillsregistry.net/v1/skills/leonwangg1-sendiment

## Description

MCP server giving AI agents persistent, self-cleaning memory across sessions. Forgets the stale, merges duplicates, resolves contradictions.

## Trust

- **Trust score (0–1):** 0.92
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/leonwangg1/sendiment)

## 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": "leonwangg1-sendiment"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/leonwangg1-sendiment` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/leonwangg1-sendiment/pull`

---
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