Competition Queue Worker Drift

CommunityPopular

zhaoxuya520

competition-queue-worker-drift

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for queues, async workers, cron jobs, delayed tasks, retry behavior, worker-only config drift, and payload-to-side-effect chains. Use when the user asks to trace a queue payload, inspect async job execution, explain worker-only behavior, follow retries or dead-letter handling, or connect an enqueued item to a later file, cache, email, or privilege-bearing side effect. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Overview

Publisher	zhaoxuya520
Repository	`reverse-skill`
Skill name	`competition-queue-worker-drift`
Stars	36.3K
Forks	5K
Bundled files	2
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by zhaoxuya520 on GitHub. Read the source before you install it.

Installation

Install the Competition Queue Worker Drift AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-queue-worker-drift

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/zhaoxuya520/reverse-skill.git /tmp/reverse-skill
mkdir -p .claude/skills
cp -r /tmp/reverse-skill/CTF-Sandbox-Orchestrator/competition-queue-worker-drift .claude/skills/competition-queue-worker-drift

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competition Queue Worker Drift in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Competition Queue Worker Drift on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Competition Queue Worker Drift is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Competition Queue Worker Drift

Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.

Use this skill when the decisive effect happens after enqueue, inside a worker, or only under async runtime state that differs from the request path.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

Map the async chain first: enqueue point, queue payload, worker consumer, retries, and final side effect.
Keep request-time state separate from worker-time state.
Record queue name, message shape, worker config, retry policy, and downstream store in one chain.
Compare synchronous path and async path when behavior diverges.
Reproduce the smallest enqueue-to-side-effect flow that proves the decisive async drift.

Workflow

1. Map Enqueue And Worker Identity

Record queue names, topics, cron schedules, delayed jobs, dead-letter queues, worker processes, and consumer groups.
Note which config, env vars, feature flags, or credentials exist only in the worker environment.
Keep enqueue request, stored payload, and worker identity tied together.

2. Trace Worker-Only State And Retries

Show how worker runtime differs from the request path: different env, files, mounts, caches, permissions, or clocks.
Record retry count, backoff, dedupe keys, failure handling, dead-letter flow, and idempotency behavior.
Distinguish immediate request success from eventual worker success or failure.

3. Reduce To The Decisive Async Chain

Compress the result to the smallest sequence: enqueue -> worker runtime -> retry or branch -> resulting effect.
State clearly whether the decisive difference lives in payload shape, worker config, retry path, or downstream consumer.
If the issue is really about the file parser invoked by the worker, switch back to the tighter file-parser skill.

Read This Reference

Load references/queue-worker-drift.md for the queue checklist, retry checklist, and evidence packaging.

What To Preserve

Queue names, payloads, worker identities, retry metadata, dead-letter edges, and downstream effects
The exact worker-only config or state that changes behavior
One minimal enqueue-to-side-effect reproduction chain

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

agents/openai.yaml1 KB
references/queue-worker-drift.md1 KB

Frequently asked questions

What does the Competition Queue Worker Drift AI skill do?

Why use Competition Queue Worker Drift on TypingMind?

Because you install it once and use it with any model. Competition Queue Worker Drift is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Competition Queue Worker Drift in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-queue-worker-drift. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Competition Queue Worker Drift?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Competition Queue Worker Drift?

As many as you like. As long as a model supports skills, you can use Competition Queue Worker Drift with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Competition Queue Worker Drift AI skill free?

Yes. It is published on GitHub by zhaoxuya520 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Competition Queue Worker Drift

Quick Start

Workflow

1. Map Enqueue And Worker Identity

2. Trace Worker-Only State And Retries

3. Reduce To The Decisive Async Chain

Read This Reference

What To Preserve

Bundled files

Frequently asked questions

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