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 lensesio/agentic-engineering-for-apache-kafka --skill kafka-schema-reviewgit clone --depth 1 https://github.com/lensesio/agentic-engineering-for-apache-kafkaWrote 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/lensesio/agentic-engineering-for-apache-kafka/kafka-schema-review)<a href="https://agentmods.dev/skills/lensesio/agentic-engineering-for-apache-kafka/kafka-schema-review"><img src="https://agentmods.dev/badge/skills/lensesio/agentic-engineering-for-apache-kafka/kafka-schema-review/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/lensesio/agentic-engineering-for-apache-kafka/kafka-schema-review"><img src="https://agentmods.dev/badge/skills/lensesio/agentic-engineering-for-apache-kafka/kafka-schema-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00089 | $0.01550 |
| Opus 5 | $0.00044 | $0.00775 |
| Sonnet 5 | $0.00018 | $0.00310 |
| Haiku 4.5 | $0.00009 | $0.00155 |
Grade A, and why
kafka-schema-review 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 12d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kafka Schema Evolution Review
Reviews schema changes for compatibility and evolution best practices. A single breaking schema change can take down every consumer of a topic.
Target environment: $ARGUMENTS
Workflow
Copy this checklist and track your progress:
Schema Review Progress:
- [ ] Step 1: Fetch registered schemas
- [ ] Step 2: Scan codebase for schema files
- [ ] Step 3: Detect breaking changes
- [ ] Step 4: Check schema quality
- [ ] Step 5: Check schema drift
- [ ] Step 6: Generate report
- Fetch registered schemas from the live cluster via Lenses MCP
- Scan codebase for schema definition files (see
references/compatibility-rules.mdfor file types) - Detect breaking changes against compatibility rules in
references/compatibility-rules.md - Check schema quality against best practices
- Check schema drift between repo and cluster
- Report findings with migration guidance
Step 1: Fetch Registered Schemas
Use Lenses MCP tools to get the current state of schemas in the cluster:
list_topic_metadata- get all schemas registered against topics (key and value)get_topic_metadata- get the current schema for a specific topicget_dataset- get dataset field-level details, policies and governance metadatalist_datasetswithschema_formatfilter - find all topics using a given format (AVRO, JSON, PROTOBUF)
Expected output: Map of topics to their registered schemas (key and value) with format and version info.
Validation: If no schemas are registered, note this as a governance gap and proceed with codebase-only analysis.
Step 2: Codebase Inspection
Search the codebase for schema definition files. Consult references/compatibility-rules.md for the full list of file types and search patterns.
Use git diff to identify recently changed schema files if reviewing a PR.
Step 3: Compatibility Checks
For each schema change, evaluate against the compatibility rules in references/compatibility-rules.md. Check backward, forward and full compatibility depending on the topic's configured compatibility level.
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.
- 12d ago First seen · 174 lines · 89 tokens per session scan A 78619485ecc7
kafka-schema-review is a skill published in the GitHub repository lensesio/agentic-engineering-for-apache-kafka (57 stars, last pushed 21d ago), licensed MIT. It adds 89 tokens to every session and 1,550 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 2026-08-30.
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