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 skills/vaquarkhan/data-engineering-agent-skills/java-data-engineering-and-integration-servicesnpx skills add vaquarkhan/data-engineering-agent-skills --skill java-data-engineering-and-integration-servicesgit 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/java-data-engineering-and-integration-services)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/java-data-engineering-and-integration-services"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/java-data-engineering-and-integration-services.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 | $0.00045 | $0.00661 |
| Opus 5 | $0.00023 | $0.00331 |
| Sonnet 5 | $0.00009 | $0.00132 |
| Haiku 4.5 | $0.00005 | $0.00066 |
Grade A, and why
java-data-engineering-and-integration-services 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.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Java Data Engineering And Integration Services
Overview
Use this skill when Java is the main implementation language for data-adjacent services or processing components. It helps agents design operationally safe JVM services for ingestion, metadata, contracts, stream handling, connectors, and control-plane style data tooling with deliberate resource, dependency, and concurrency management.
When to Use
- building ingestion or connector services in
Java - implementing JVM-based stream processors or integration utilities
- exposing data-platform metadata, contract, or control services
- managing
MavenorGradlebuilds for data-related services - debugging resource, thread, serialization, or connection-pool behavior in JVM services
Do not treat Java services as generic app code when they carry data-delivery, contract, or pipeline semantics.
Workflow
-
Define the service role and operational boundary. Clarify:
- request or event model
- upstream and downstream systems
- throughput and latency expectations
- delivery guarantees
- retry and failure behavior
-
Make contracts explicit. Include:
- payload schemas
- versioning behavior
- idempotency rules
- error model
- compatibility with downstream consumers
-
Design resource and concurrency behavior deliberately. Review:
- thread pools
- blocking versus async paths
- connection management
- backpressure
- graceful shutdown and restart behavior
-
Package and configure for operations. Decide:
MavenorGradleconventions- dependency version strategy
- environment configuration
- secrets handling
- observability and health signals
-
Validate service behavior under realistic load and failure conditions. Require:
- contract checks
- retry and timeout tests
- connection and resource sanity
- release and rollback readiness
Common Rationalizations
| Rationalization | Reality |
|---|---|
| "The framework defaults are good enough." | Defaults for thread pools, connection pools, and retries often fail under data-heavy or bursty workloads. |
| "It is just a connector wrapper." | Connectors still define contracts, error handling, retries, and downstream correctness. |
| "Java is verbose but safe by default." | JVM services still fail due to resource leaks, blocking calls, schema drift, and weak operational boundaries. |
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 · 85 lines · 45 tokens per session scan A 3c4ed3aacda5
java-data-engineering-and-integration-services is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (40 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 661 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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