# context-anchor

> Use this tool when you need to recover from context compaction by scanning memory files to restore lost context and improve system performance. It solves problems related to memory file corruption and context loss, providing a reliable way to rebuild and recover compacted data. The context-anchor tool takes memory files as input and outputs restored context, making it ideal for use in situations where data integrity and system stability are critical.

Canonical page: https://skillsregistry.net/skills/boscoeuk-context-anchor  
JSON: https://api.skillsregistry.net/v1/skills/boscoeuk-context-anchor

## Description

Recover from context compaction by scanning memory files.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** file-system
- **Updated:** 2026-09-19

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/boscoeuk-context-anchor)

## 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": "boscoeuk-context-anchor"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/boscoeuk-context-anchor` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/boscoeuk-context-anchor/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