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.
git clone --depth 1 https://github.com/d-padmanabhan/agent-engineering-handbookWrote 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/rules/d-padmanabhan/agent-engineering-handbook/483-kafka)<a href="https://agentmods.dev/rules/d-padmanabhan/agent-engineering-handbook/483-kafka"><img src="https://agentmods.dev/badge/rules/d-padmanabhan/agent-engineering-handbook/483-kafka.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 5.1 | $0.00023 | $0.00851 |
| Opus 5 | $0.00012 | $0.00426 |
| Sonnet 5 | $0.00005 | $0.00170 |
| Haiku 4.5 | $0.00002 | $0.00085 |
Grade A, and why
483-kafka scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kafka Engineering Ruleset (Confluent)
Audience: engineers building Kafka-backed streaming systems and event-driven pipelines
Goal: predictable delivery semantics, governed schemas, safe retries, and observable operations
Delivery semantics (be explicit)
- Default is at-least-once. Design consumers to be idempotent.
- If you truly need “exactly-once”, define what that means end-to-end (Kafka transactions alone may not be sufficient).
For cross-service consistency, Transactional Outbox/Inbox, Saga orchestration/choreography, compensation, and dual-write remediation, use the distributed transactions skill (${HANDBOOK_ROOT}/skills/distributed-transactions/SKILL.md).
Consumer idempotency (default expectation)
- Use stable event identifiers and de-dup at the sink or state store.
- Avoid side effects before commit unless you can safely retry.
Topic design
- Partitioning is an API contract:
- key choice determines ordering guarantees
- partition count affects parallelism and rebalancing
- Set retention intentionally:
- time-based retention for event history
- compaction for “latest state by key”
- Keep message size bounded; large payloads increase latency and cost.
[!IMPORTANT] Changing topic key semantics is a breaking change for consumers.
Schema governance (Schema Registry)
- Prefer strongly-defined schemas (Avro/Protobuf/JSON Schema) over “schemaless JSON”.
- Enforce compatibility mode per subject (backward/forward/full) aligned to your evolution policy.
- Treat breaking schema changes like migrations:
- versioned subjects or dual-publish
- coordinated consumer rollout
Producer patterns
- Prefer idempotent producers when duplicates are harmful.
- Treat retries and timeouts as first-class configuration; define limits.
- If ordering matters, ensure keying and partition strategy preserve it.
Consumer patterns
- Choose commit strategy explicitly:
- commit after processing (common)
- combine the business effect and durable Inbox/Outbox state in one local transaction when needed
- Retry strategy must avoid infinite poison-pill loops:
- bounded retries with backoff
- dead-letter topic (DLT/DLQ) for quarantining
- Rebalancing and lag must be monitored.
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.
- 4d ago First seen · 125 lines · 23 tokens per session scan A 4cbea3bf2ae6
483-kafka is a cursor rule published in the GitHub repository d-padmanabhan/agent-engineering-handbook (16 stars, last pushed yesterday), licensed MIT. It adds 23 tokens to every session and 851 once invoked, about $0.0001 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 2026-09-03.
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