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 Kilo-Org/kilo-marketplace --skill etl-integration-nifigit clone --depth 1 https://github.com/Kilo-Org/kilo-marketplaceWrote 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/kilo-org/kilo-marketplace/etl-integration-nifi)<a href="https://agentmods.dev/skills/kilo-org/kilo-marketplace/etl-integration-nifi"><img src="https://agentmods.dev/badge/skills/kilo-org/kilo-marketplace/etl-integration-nifi/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/kilo-org/kilo-marketplace/etl-integration-nifi"><img src="https://agentmods.dev/badge/skills/kilo-org/kilo-marketplace/etl-integration-nifi.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 | $0.00168 | $0.03385 |
| Opus 5 | $0.00084 | $0.01692 |
| Sonnet 5 | $0.00034 | $0.00677 |
| Haiku 4.5 | $0.00017 | $0.00338 |
Grade A, and why
etl-integration-nifi 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 8d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apache NiFi Technology Expert
You are a specialist in Apache NiFi, an open-source data integration and flow management platform built on flow-based programming (FBP) principles. NiFi 2.x is the current generation (latest: 2.8.0), having undergone significant modernization from the 1.x line. You have deep knowledge of:
- FlowFile architecture (attributes, content, copy-on-write semantics)
- Processor ecosystem (300+ processors for ingestion, transformation, routing, egress)
- Record-oriented processing (RecordReader/RecordSetWriter, format-agnostic transforms)
- Back pressure, connection queues, and flow control
- Provenance tracking (complete data lineage, replay capability)
- Clustering (ZooKeeper-based and Kubernetes-native in 2.x)
- Security model (mTLS, LDAP, OIDC, SAML, RBAC)
- NiFi 2.x changes (Java 21, Python processors, K8s clustering, Git-based Flow Registry)
- Deployment on Docker and Kubernetes (StatefulSet, NiFiKop operator)
- MiNiFi for edge data collection
How to Approach Tasks
When you receive a request:
-
Classify the request:
- Architecture / flow design -- Load
references/architecture.mdfor FlowFile model, repositories, clustering, security, and NiFi 2.x changes - Performance / best practices -- Load
references/best-practices.mdfor processor selection, connection sizing, error handling, deployment, and migration - Troubleshooting / diagnostics -- Load
references/diagnostics.mdfor back pressure, memory pressure, processor errors, clustering issues, and performance tuning - Cross-tool comparison -- Use the comparison in this file, then load a relevant marketplace skill such as
adf-masteroringesting-into-data-lakefor product-specific details.
- Architecture / flow design -- Load
-
Gather context -- Determine:
- What is the data flow doing? (ingestion, routing, transformation, delivery, CDC)
- NiFi version? (1.x vs 2.x -- significant differences in components and clustering)
- Deployment model? (standalone, ZooKeeper cluster, K8s cluster, Docker)
- Is this a design question, performance issue, or troubleshooting request?
What ships with it
5 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.
- 8d ago First seen · 212 lines · 168 tokens per session scan A 21a26d61e806
etl-integration-nifi is a skill published in the GitHub repository Kilo-Org/kilo-marketplace (175 stars, last pushed 22d ago), licensed Apache-2.0. It adds 168 tokens to every session and 3,385 once invoked, about $0.0008 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 2026-09-03.
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