# effectfence

> effectfence — aurumflux20-effectfence. Use this tool when you need to prevent duplicate executions of side effects, such as double-charges or duplicate sends, and ensure that only one agent wins in same-instant races. The effectfence tool takes in preparation, commitment, and abortion inputs through fence_prepare, fence_commit, and fence_abort, and outputs a sealed receipt to prevent late duplicates from executing again. It is ideal for use cases where concurrent agent actions may cause unintended consequences, providing a reliable and efficient solution to mitigate these issues.

Canonical page: https://skillsregistry.net/skills/aurumflux20-effectfence  
JSON: https://api.skillsregistry.net/v1/skills/aurumflux20-effectfence

## Description

Stops agents double-firing side effects like double-charges or duplicate sends: same-instant races elect exactly one winner, and late duplicates get a sealed, content-addressed receipt replayed instead of a second execution. Tools: fence_prepare, fence_commit, fence_abort.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/q1xibacd7n)
- **Repository:** <https://github.com/aurumflux20/effectfence>

## 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": "aurumflux20-effectfence"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/aurumflux20-effectfence` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/aurumflux20-effectfence/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