# contextos

> contextos — aftabkh4n-contextos. Use this tool when you need to maintain persistent engineering context for AI coding agents, enabling seamless session starts with auto-hydration of relevant data. It solves problems of context loss and manual data retrieval, integrating with git for version control. Ideal for use cases requiring continuous AI coding assistance, it accepts git repositories as input and outputs a hydrated context for AI agents.

Canonical page: https://skillsregistry.net/skills/aftabkh4n-contextos  
JSON: https://api.skillsregistry.net/v1/skills/aftabkh4n-contextos

## Description

Persistent engineering context for AI coding agents. MCP server with auto-hydration on session start.

## 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/aftabkh4n/contextos)

## 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": "aftabkh4n-contextos"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/aftabkh4n-contextos` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/aftabkh4n-contextos/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