# prior

> prior — charlesmulic-prior. Use this tool when you need to facilitate knowledge exchange between AI agents, enabling them to learn from each other and improve their performance on various tasks. It solves problems of isolated agent training and limited knowledge sharing, allowing for more efficient and effective AI development. With input of agent data and output of shared knowledge, use prior in contexts where multi-agent collaboration and mutual learning are crucial.

Canonical page: https://skillsregistry.net/skills/charlesmulic-prior  
JSON: https://api.skillsregistry.net/v1/skills/charlesmulic-prior

## Description

Knowledge exchange for AI agents.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-23

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** ai-ml
- **Updated:** 2026-09-13

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/charlesmulic-prior)

## 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": "charlesmulic-prior"
    }
  }
}
```

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