competition-queue-worker-drift

A CTF workflow for tracing work that moves from a request into a queue and is later handled by a worker. A queue stores jobs until another process runs them.

In plain words
What is it for?
Use it to investigate queue messages, asynchronous workers, scheduled tasks, delayed jobs, retry handling, dead-letter queues, and worker-only configuration.
Why use it?
It helps explain behavior that appears only in background jobs, including different configuration, retries, timing, or side effects.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/2233admin/reverse-skill-evolver/competition-queue-worker-drift
Any agent
npx skills add 2233admin/reverse-skill-evolver --skill competition-queue-worker-drift
Clone the repo
git clone --depth 1 https://github.com/2233admin/reverse-skill-evolver

Made for: Claude Code, Codex.

Per session 121 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 625 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00121 $0.00625
Opus 5 $0.00060 $0.00313
Sonnet 5 $0.00024 $0.00125
Haiku 4.5 $0.00012 $0.00063

Measured 2d ago against content hash e39356ec96f3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

competition-queue-worker-drift scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to competition-queue-worker-drift — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

CTF-Sandbox-Orchestrator/competition-queue-worker-drift/SKILL.md · 51 lines

How it starts

The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

  1. Map the async chain first: enqueue point, queue payload, worker consumer, retries, and final side effect.
  2. Keep request-time state separate from worker-time state.
  3. Record queue name, message shape, worker config, retry policy, and downstream store in one chain.
  4. Compare synchronous path and async path when behavior diverges.
  5. 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 the full file on GitHub · 51 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 51 lines · 121 tokens per session scan A e39356ec96f3

Subscribe to this mod's changes

competition-queue-worker-drift is a skill published in the GitHub repository 2233admin/reverse-skill-evolver (13 stars, last pushed 21d ago), licensed MIT. It adds 121 tokens to every session and 625 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to competition-queue-worker-drift, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens