# pawrecall

> pawrecall — chaucerj-pawrecall. Use this tool when you need to search and recall conversation history across AI agents, solving issues of lost context and information. It provides a simple interface for searching and retrieving past conversations, accepting text inputs and returning relevant conversation history as output. Ideal for use cases where conversation tracking and recall are crucial, such as customer support or knowledge management.

Canonical page: https://skillsregistry.net/skills/chaucerj-pawrecall  
JSON: https://api.skillsregistry.net/v1/skills/chaucerj-pawrecall

## Description

🐾 Every conversation leaves a print. Cross-agent AI conversation history search — one Python file, zero deps, MCP + CLI + skill, perfect CJK.

## Trust

- **Trust score (0–1):** 0.86
- **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/chaucerj/pawrecall)

## 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": "chaucerj-pawrecall"
    }
  }
}
```

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