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/mickeyyaya/refactoring-skills/message-queue-patternsnpx skills add mickeyyaya/refactoring-skills --skill message-queue-patternsgit clone --depth 1 https://github.com/mickeyyaya/refactoring-skillsWrote 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/mickeyyaya/refactoring-skills/message-queue-patterns)<a href="https://agentmods.dev/skills/mickeyyaya/refactoring-skills/message-queue-patterns"><img src="https://agentmods.dev/badge/skills/mickeyyaya/refactoring-skills/message-queue-patterns.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 | $0.00086 | $0.04321 |
| Opus 5 | $0.00043 | $0.02160 |
| Sonnet 5 | $0.00017 | $0.00864 |
| Haiku 4.5 | $0.00009 | $0.00432 |
Grade A, and why
message-queue-patterns 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.
How it starts
The opening of the file, as written. The whole thing — 468 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Message Queue and Event-Driven Messaging Patterns
Overview
Message queues decouple producers from consumers, enabling async processing, horizontal scaling, and fault isolation. Incorrect delivery semantics, dual-write hazards, unordered processing, and unbounded queues are among the most costly bugs in distributed systems.
When to use: Building async workflows, microservice integrations, event streaming pipelines, background job processors, or any system where services communicate without direct RPC calls.
Quick Reference
| Pattern | Core Idea | Primary Red Flag |
|---|---|---|
| Point-to-Point | One producer, one consumer per message | Multiple consumers competing without coordination |
| Publish-Subscribe | One producer, many independent consumers | Consumers sharing state or needing ordered delivery |
| Competing Consumers | Multiple workers drain a single queue | No idempotency guard — duplicate processing |
| At-Most-Once | Fire and forget; may lose messages | Using for financial or critical-state updates |
| At-Least-Once | Retry until ack; may duplicate | No idempotency key on consumer side |
| Exactly-Once | Transactional guarantee; no loss, no dup | Ignoring overhead — exactly-once is expensive |
| Transactional Outbox | Write event to DB in same transaction as state | Dual-write without outbox — partial failures |
| Dead Letter Queue | Route unprocessable messages for inspection | Silently dropping poison pill messages |
| Kafka Partitions | Ordered log per partition; parallelism by partition count | Hot partitions, wrong partition key, too few partitions |
| Backpressure | Slow consumers signal producers to slow down | Unbounded in-memory queues causing OOM |
Patterns in Detail
1. Point-to-Point vs Publish-Subscribe
Point-to-Point (Queue): Each message delivered to exactly one consumer. Use for task distribution — work orders, command processing. Publish-Subscribe (Topic): Each message delivered to all subscribers. Use for event broadcasting — audit logs, cache invalidation, projections.
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 · 468 lines · 86 tokens per session scan A a9e7e9bbfb8a
message-queue-patterns is a skill published in the GitHub repository mickeyyaya/refactoring-skills (6 stars, last pushed 5mo ago), licensed MIT. It adds 86 tokens to every session and 4,321 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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