# Sensei

> Use this tool when you need to provide personalized learning experiences, adaptive explanations, and avoid redundant information. Sensei solves the problem of repetitive explanations by storing user skills, learning history, and project context, and outputs tailored guidance. It is ideal for use cases where users require customized support and context-aware feedback.

Canonical page: https://skillsregistry.net/skills/codebyellalesperance-sensei  
JSON: https://api.skillsregistry.net/v1/skills/codebyellalesperance-sensei

## Description

Provides Claude with persistent memory about the user's skills, learning history, and project context to deliver personalized, adaptive explanations and avoid repeating basics.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ilmx19kj1q)
- **Repository:** <https://github.com/codebyellalesperance/sensei>

## 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": "codebyellalesperance-sensei"
    }
  }
}
```

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