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 skills add vaquarkhan/data-engineering-agent-skills --skill kafka-resilience-and-schema-evolutiongit clone --depth 1 https://github.com/vaquarkhan/data-engineering-agent-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/vaquarkhan/data-engineering-agent-skills/kafka-resilience-and-schema-evolution)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/kafka-resilience-and-schema-evolution"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/kafka-resilience-and-schema-evolution/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/kafka-resilience-and-schema-evolution"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/kafka-resilience-and-schema-evolution.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00057 | $0.00984 |
| Opus 5 | $0.00028 | $0.00492 |
| Sonnet 5 | $0.00011 | $0.00197 |
| Haiku 4.5 | $0.00006 | $0.00098 |
Grade A, and why
kafka-resilience-and-schema-evolution 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 11d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kafka Resilience And Schema Evolution
Overview
Generic streaming guidance is not enough for production Kafka. Agents routinely introduce breaking schema changes, under-provisioned durability settings, and missing poison-message isolation. This skill mandates enforceable broker, producer, consumer, and registry guardrails before any production change ships.
When to Use
- creating or modifying
Kafkatopics, producers, or consumers - setting or changing schema registry compatibility policies
- designing dead-letter queue (DLQ) routing for poison pill messages
- hardening producer durability (
acks, retries, idempotence) - reviewing consumer lag, replay, or failover behavior on Kafka-backed pipelines
Pair with streaming-and-messaging-systems for broader event design. Pair with avro-protobuf-json-schema-registry when registry subjects and compatibility CI are in scope.
Workflow
-
Define the production contract before broker changes. Document:
- topic key strategy and partition count rationale
- retention, compaction, and replay policy
- schema format and registry subject naming
- consumer groups and downstream sinks
- delivery semantics target (at-least-once with idempotent sinks, or stricter)
-
Enforce producer durability defaults. Require unless explicitly waived with owner approval:
acks=all(oracks=-1)enable.idempotence=truewhen ordering and deduplication matter- bounded
retrieswithdelivery.timeout.msaligned to SLA max.in.flight.requests.per.connection=1when strict ordering is required- TLS/SASL configuration documented for non-development clusters
-
Block breaking schema evolution. Before any schema change:
- set compatibility policy per subject (
BACKWARD,FORWARD, orFULL— notNONEin production) - run compatibility checks in CI against registered schemas
- document producer-then-consumer or consumer-then-producer rollout order
- reject field removals, renames, or type changes without migration plan
- load
references/kafka-production-guardrails.mdfor DLQ and evolution patterns
- set compatibility policy per subject (
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.
- 11d ago First seen · 91 lines · 57 tokens per session scan A fb5cb00eca66
kafka-resilience-and-schema-evolution is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (45 stars, last pushed 2mo ago), licensed MIT. It adds 57 tokens to every session and 984 once invoked, about $0.0003 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 2026-08-30.
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