# shpbl-spec-drift-sentinel

> shpbl-spec-drift-sentinel — sweetkenneth-shpbl-spec-drift-sentinel. Use this tool when you need to detect and explain deviations in AI agent behavior from their specified norms, solving issues of unintended drift and ensuring reliability. It takes in agent behavior data and specification guidelines as inputs, producing outputs that highlight drift occurrences and provide explanations. Ideal for use in monitoring and maintaining AI systems, particularly when agent behavior needs to align with predefined standards.

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

## Description

Specification only: explainable detection of agent behavior drift.

## Trust

- **Trust score (0–1):** 0.96
- **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-spec-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-spec-drift-sentinel"
    }
  }
}
```

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