# joa

> Use this tool when you need to track and analyze AI decision-making processes over time. It solves problems of accountability, transparency, and debugging by logging decisions, changes, errors, and observations, and allows querying of this data across sessions. The tool accepts log entries as input and provides searchable records as output, making it ideal for use in complex, multi-session AI applications.

Canonical page: https://skillsregistry.net/skills/neethanwu-joa  
JSON: https://api.skillsregistry.net/v1/skills/neethanwu-joa

## Description

Persistent activity journal for AI agents - enables logging and querying decisions, changes, errors, and observations across sessions.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/n4s4okkpc7)
- **Repository:** <https://github.com/neethanwu/joa>

## 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": "neethanwu-joa"
    }
  }
}
```

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