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.
npx agentmods add skills/asaiuta/reverse-workbench-skill/competition-queue-worker-driftnpx skills add Asaiuta/reverse-workbench-skill --skill competition-queue-worker-driftgit clone --depth 1 https://github.com/Asaiuta/reverse-workbench-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/competition-queue-worker-drift)<a href="https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/competition-queue-worker-drift"><img src="https://agentmods.dev/badge/skills/asaiuta/reverse-workbench-skill/competition-queue-worker-drift.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once 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 |
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 3d 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.
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.
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
- 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.
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.
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.
- 3d ago First seen · 51 lines · 121 tokens per session scan A e39356ec96f3
competition-queue-worker-drift is a skill published in the GitHub repository Asaiuta/reverse-workbench-skill (2 stars, last pushed 20d 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.
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