# agent-invariants

> agent-invariants — christian140903-sudo-agent-invariants. Use this tool when you need to ensure consistent behavior of AI agents across different scenarios, solving problems of regression detection and compliance with operating contracts. It checks event traces against predefined rules, providing inputs of normalized event data and outputs of compatibility reports. Use it in contexts where deterministic behavior and contract adherence are crucial, such as in high-stakes decision-making or safety-critical applications.

Canonical page: https://skillsregistry.net/skills/christian140903-sudo-agent-invariants  
JSON: https://api.skillsregistry.net/v1/skills/christian140903-sudo-agent-invariants

## Description

A deterministic behavior-compatibility layer for AI agents that checks normalized event traces against operating contracts and compares baselines with candidates to catch regressions in approval, stop, scope, recovery, and completion rules.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/zf5t2mlhah)
- **Repository:** <https://github.com/christian140903-sudo/agent-invariants>

## 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": "christian140903-sudo-agent-invariants"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/christian140903-sudo-agent-invariants` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/christian140903-sudo-agent-invariants/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