AI Agent Skills by Confluent is a collection of skills for building Kafka producers, Flink applications, and real-time data-streaming pipelines. Developers use it with coding assistants when creating applications and pipelines on Confluent. The catalogue entries are its skills, plugin, and instruction.
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 confluentinc/agent-skills --skill inlined-refsgit clone --depth 1 https://github.com/confluentinc/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/confluentinc/agent-skills/inlined-refs)<a href="https://agentmods.dev/skills/confluentinc/agent-skills/inlined-refs"><img src="https://agentmods.dev/badge/skills/confluentinc/agent-skills/inlined-refs.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 | $0.00054 | $0.00314 |
| Opus 5 | $0.00027 | $0.00157 |
| Sonnet 5 | $0.00011 | $0.00063 |
| Haiku 4.5 | $0.00005 | $0.00031 |
Grade A, and why
inlined-refs 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 7d 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
inlined-refs — consumer lag dashboarding
Step 1 — pick the exporter
We support two exporters. Read the comparison below before recommending.
Exporter comparison (from references/exporters.md)
kafka-exporter (Danielqsj)
Pros: lightweight, single binary, exposes per-group lag directly.
Cons: stateful (consumes __consumer_offsets internally), can lag on large clusters.
Best for: clusters < 100 brokers, < 1000 consumer groups.
Config snippet:
kafka-exporter \
--kafka.server=localhost:9092 \
--kafka.version=3.5.0 \
--web.listen-address=:9308
Confluent Control Center
Pros: official, covers full Confluent Platform metrics. Cons: paid licensing, heavier footprint.
Best for: enterprise Confluent Platform users.
Step 2 — Grafana dashboard
Use Grafana dashboard 7589 for kafka-exporter. Filter by consumer group, plot kafka_consumergroup_lag over a 5-minute window.
Step 3 — alerts
Set lag > 10,000 messages for 5 minutes as the default alert. Adjust per topic SLA.
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.
- 7d ago First seen · 43 lines · 54 tokens per session scan A ca6dffe3c178
inlined-refs is a skill published in the GitHub repository confluentinc/agent-skills (54 stars, last pushed 3d ago), licensed Apache-2.0. It adds 54 tokens to every session and 314 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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