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 wardawgmalvicious/agent-config --skill fabric-eventstreamgit clone --depth 1 https://github.com/wardawgmalvicious/agent-configWrote 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/wardawgmalvicious/agent-config/fabric-eventstream)<a href="https://agentmods.dev/skills/wardawgmalvicious/agent-config/fabric-eventstream"><img src="https://agentmods.dev/badge/skills/wardawgmalvicious/agent-config/fabric-eventstream/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/wardawgmalvicious/agent-config/fabric-eventstream"><img src="https://agentmods.dev/badge/skills/wardawgmalvicious/agent-config/fabric-eventstream.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 | $0.00242 | $0.02518 |
| Opus 5 | $0.00121 | $0.01259 |
| Sonnet 5 | $0.00048 | $0.00504 |
| Haiku 4.5 | $0.00024 | $0.00252 |
Grade A, and why
fabric-eventstream 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 today.
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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fabric Eventstream
Streaming-data ingestion item that pulls events from a wide source surface (CDC / Event Hubs / Kafka / IoT / HTTP / MQTT) and routes them into Fabric destinations (Lakehouse, Eventhouse, Activator, derived stream, custom endpoint). Authoring is graph-based: source nodes → optional transformations → destination nodes, edited then published to go live.
When to use vs not
Use Eventstream when the data is arriving as events and needs routing or transformation before it lands. Skip it when the data is bulk / batch (use a Data Pipeline Copy activity), already in the lake (use Spark / SQL directly), or when the only consumer is a Mirrored Database in append-only mode (mirroring lands data straight in OneLake without an Eventstream).
For real-time analytics on the resulting events, pair an Eventstream with fabric-eventhouse (KQL Database). For real-time rules, pair with an Activator destination (covered below).
Authoring model
- Edit mode vs Live mode: changes only take effect after Publish. New nodes added in Edit mode produce no traffic until publish.
- Sources = where events come from. Transformations = inline filter / aggregate / GroupBy / Manage Fields / SQL. Destinations = where events go. Each destination can have its own format (Delta / JSON / Avro) where applicable.
- Permissions: workspace Contributor or higher to author; Viewer can read Data insights monitoring on a published stream.
- Virtual-network injection (private-network sources): use Eventstream connector VNet injection for sources behind a firewall — see Microsoft Learn.
Sources
Grouped by what you have to get right, not by vendor. Full connector table with per-source notes: references/source-connectors.md.
| Family | Connectors | The thing that bites |
|---|---|---|
| Database CDC | Azure SQL, SQL MI, SQL Server on VM, PostgreSQL, MySQL, MongoDB (preview), Cosmos DB | Azure SQL needs sys.sp_cdc_enable_db; you cannot enable Mirroring and Eventstream CDC on the same database |
| Mirrored DB Delta CDF | Mirrored Database (preview, April 2026) | Row-level CDC off a Mirrored DB's Delta Change Data Feed — opt in per database |
| Native Azure | Event Hubs, IoT Hub | Auth is Shared Access Key; workspace-identity auth is preview (Aug 2026) and the UI leads the docs |
| Kafka protocol | Apache Kafka, Amazon MSK, Confluent Cloud | GA June 2026. Custom CA / mTLS GA July 2026 — Kafka-family only |
| Other cloud / broker | Kinesis, Service Bus, Google Pub/Sub, Solace PubSub+ | Service Bus GA June 2026 |
| Protocol / pull | MQTT (preview), HTTP (preview), Azure Data Explorer, Real-time weather | HTTP ships predefined public feeds for testing |
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.
- today Changed 0785302e227f
- 6d ago Changed · -114 lines ff1dba4b4fcc
- 10d ago First seen · 267 lines · 242 tokens per session scan A 845e16feea25
fabric-eventstream is a skill published in the GitHub repository wardawgmalvicious/agent-config (1 stars, last pushed today), licensed MIT. It adds 242 tokens to every session and 2,518 once invoked, about $0.0012 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 2026-08-31.
Other skills, from other repositories
marketing-strategy-pmm
Product marketing, positioning, GTM strategy, and competitive intelligence. Includes ICP definition, April Dunford positioning methodology, launch playbooks, competitive battlecards, and international market entry guides. Use when developing positioning, planning product launches, creating messaging, analyzing…
loki-mode
Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention.…
email-sequence
When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle…
qa-test-planner
Generate comprehensive test plans, manual test cases, regression test suites, and bug reports for QA engineers. Includes Figma MCP integration for design validation.
content-research-writer
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
training-llms-megatron
Trains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies. Use when training models >1B parameters, need maximum GPU efficiency (47% MFU on H100), or require tensor/pipeline/sequence/context/expert parallelism. Production-ready framework used for Nemotron, LLaMA…