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 ibm-self-serve-assets/building-blocks --skill data-streaming-confluent-terraformgit clone --depth 1 https://github.com/ibm-self-serve-assets/building-blocksWrote 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/ibm-self-serve-assets/building-blocks/data-streaming-confluent-terraform)<a href="https://agentmods.dev/skills/ibm-self-serve-assets/building-blocks/data-streaming-confluent-terraform"><img src="https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/data-streaming-confluent-terraform/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/ibm-self-serve-assets/building-blocks/data-streaming-confluent-terraform"><img src="https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/data-streaming-confluent-terraform.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00064 | $0.07215 |
| Opus 5 | $0.00032 | $0.03608 |
| Sonnet 5 | $0.00013 | $0.01443 |
| Haiku 4.5 | $0.00006 | $0.00722 |
Grade A, and why
data-streaming-confluent-terraform 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 11d 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.
This is a copy
97% identical to confluent-iac-terraform — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 914 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Confluent Cloud Streaming System Builder
Purpose
This skill defines the process for analyzing streaming use case requirements and generating complete, production-ready streaming systems on Confluent Cloud that include:
- Terraform Infrastructure-as-Code for Confluent Cloud resources
- Apache Flink SQL for real-time stream processing
- Python producers with proper schema serialization
- Comprehensive documentation and testing approaches
Objective
Transform natural language streaming requirements into deployable streaming systems that:
- Can be deployed to Confluent Cloud with minimal configuration
- Follow Infrastructure-as-Code best practices
- Implement correct Flink SQL patterns for stream processing
- Include production-ready error handling and monitoring
- Provide clear documentation for reproduction
- Adapt to any streaming domain while maintaining technical correctness
Documentation Principles
IMPORTANT: Generate specifications based on user requirements and streaming best practices.
Rules:
- Analyze the user's domain and infer appropriate streaming patterns
- Design schemas that match the business entities and events
- Select aggregation patterns based on use case requirements
- Generate complete, working code without placeholders
- Include all critical technical requirements (versions, formats, RBAC)
- Provide realistic sample data for the domain
- Document testing approaches with specific queries
- State assumptions clearly when inferring requirements
Scope
This skill applies to:
- Real-time data streaming use cases
- Event-driven architectures
- Stream processing and aggregation
- IoT sensor data processing
- Financial transaction processing
- Retail inventory management
- Healthcare vitals monitoring
- Logistics tracking systems
- Any domain requiring real-time data processing
The output is a complete streaming system with Terraform, Flink SQL, Python, and documentation.
Procedure
You are a Confluent Cloud streaming architect specializing in Infrastructure-as-Code and real-time data processing. When provided with a streaming use case, generate a complete streaming system following this two-phase workflow.
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.
- 11d ago First seen · 914 lines · 64 tokens per session scan A 338e3ff77633
data-streaming-confluent-terraform is a skill published in the GitHub repository ibm-self-serve-assets/building-blocks (24 stars, last pushed yesterday), licensed Apache-2.0. It adds 64 tokens to every session and 7,215 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to confluent-iac-terraform, differing in 2 lines, and is treated as a copy.
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