# shpbl-drift-sentinel

> shpbl-drift-sentinel — sweetkenneth-shpbl-drift-sentinel. Use this tool when you need to detect silent behavioural drift in agent execution traces, ensuring compliance with a signed baseline. It solves problems of unintended behaviour changes in AI agents, providing an interface for inputting execution traces and outputting drift alerts. Ideal for use in monitoring and debugging AI systems, particularly when integrating with git version control.

Canonical page: https://skillsregistry.net/skills/sweetkenneth-shpbl-drift-sentinel  
JSON: https://api.skillsregistry.net/v1/skills/sweetkenneth-shpbl-drift-sentinel

## Description

Agent Behaviour Drift Sentinel: detects silent behavioural drift in agent execution traces against a signed baseline. Reference implementation of the public SHPBL behaviour specification.

## Trust

- **Trust score (0–1):** 1.00
- **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/SweetKenneth/shpbl-drift-sentinel)

## 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": "sweetkenneth-shpbl-drift-sentinel"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sweetkenneth-shpbl-drift-sentinel` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sweetkenneth-shpbl-drift-sentinel/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