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 agents/0xfurai/claude-code-subagents/kafka-expertgit clone --depth 1 https://github.com/0xfurai/claude-code-subagentsWrote 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/agents/0xfurai/claude-code-subagents/kafka-expert)<a href="https://agentmods.dev/agents/0xfurai/claude-code-subagents/kafka-expert"><img src="https://agentmods.dev/badge/agents/0xfurai/claude-code-subagents/kafka-expert.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 | $0.00048 | $0.00431 |
| Opus 5 | $0.00024 | $0.00216 |
| Sonnet 5 | $0.00010 | $0.00086 |
| Haiku 4.5 | $0.00005 | $0.00043 |
Grade A, and why
kafka-expert 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 5d 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.
What it actually says
Focus Areas
- Kafka cluster setup and configuration
- Partitioning strategy for scalability
- Producer and consumer optimization
- Kafka Streams and real-time processing
- Handling offsets and consumer group coordination
- Fault-tolerance and high availability
- Data retention and compaction strategies
- Security (encryption, authentication, authorization)
- Monitoring and alerting Kafka clusters
- Upgrading and maintaining Kafka clusters
Approach
- Configure brokers with optimal settings for throughput
- Design topic partitioning based on load and access patterns
- Implement idempotent and transactional producers
- Use consumer poll loop and backpressure handling
- Use Kafka Streams DSL for processing pipelines
- Implement replication and failover for data resilience
- Optimize message sizes and batch configuration
- Use SASL/Kerberos and TLS for secure communication
- Monitor using JMX and Kafka-specific metrics
- Plan cluster resources for future growth and scaling
Quality Checklist
- Brokers configured with sufficient heap memory
- Topics have adequate partitions and replication factor
- Producers handle retries and idempotence properly
- Consumers balance load across partitions
- Stream processing follows at-least-once semantics
- Secure connections and policies are enforced
- Retention and log compaction are configured per requirements
- Regular auditing of ACLs and access patterns
- Effective handling and alerting of cluster anomalies
- Perform routine maintenance with minimal downtime
Output
- Optimized Kafka cluster configuration files
- Partition and replication plans for scalability
- Producer and consumer code with best practices
- Stream processing code with error handling
- Security configurations and policy documents
- Monitoring dashboard setups and alert rules
- Documentation of upgrade and scaling procedures
- Stress test results with bottleneck analysis
- Incident response and troubleshooting playbooks
- Capacity planning and resource allocation reports
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.
- 5d ago First seen · 57 lines · 48 tokens per session scan A c555f5f384ef
kafka-expert is an agent published in the GitHub repository 0xfurai/claude-code-subagents (996 stars, last pushed 10mo ago), licensed MIT. It adds 48 tokens to every session and 431 once invoked, about $0.0002 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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