# Nahuali

> Nahuali — arakiss-nahuali. Use this tool when you need to securely store and retrieve information with transparency and accountability, solving problems of data integrity and trust in AI decision-making. Nahuali provides a local-first memory interface with inputs of agent experiences and outputs of evidence-backed recall and deterministic trust verdicts. It is ideal for use cases requiring tamper-evident audit histories and self-inspection capabilities.

Canonical page: https://skillsregistry.net/skills/arakiss-nahuali  
JSON: https://api.skillsregistry.net/v1/skills/arakiss-nahuali

## Description

Local-first memory for AI agents with evidence-backed recall, deterministic trust verdicts, self-inspection, and a tamper-evident audit history.

## Trust

- **Trust score (0–1):** 0.00
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/pi0v5ekn4h)
- **Repository:** <https://github.com/Arakiss/nahuali>

## 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": "arakiss-nahuali"
    }
  }
}
```

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