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Speech-To-Text-With-Databricks: Skill for Claude Code

.claude/skills/databricks-spark-structured-streaming/SKILL.md

databricks-spark-structured-streaming is a skill for Claude Code from alessandro9110/Speech-To-Text-With-Databricks. It costs 43 tokens per session (636 once invoked), scanned A, original, MIT.

A guide to processing continuously arriving data with Apache Spark, a system for running large-scale data jobs, including data from Kafka and storage tables.

In plain words
What is it for?
It is for building streaming pipelines, joining live and stored data, writing to multiple destinations, and improving stream processing.
Why use it?
It provides patterns for handling live data, combining streams, saving results, and managing state in production pipelines.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is alessandro9110/Speech-To-Text-With-Databricks's own configuration. It tells Claude Code how to work on Speech-To-Text-With-Databricks itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Speech-To-Text-With-Databricks configures →

not rated 4repo 8mo ago A scan 43 tokens original MIT
View source ↗ alessandro9110/Speech-To-Text-With-Databricks
Reuse

Borrowing it

Nothing to install: this file belongs to alessandro9110/Speech-To-Text-With-Databricks. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/alessandro9110/Speech-To-Text-With-Databricks/main/.claude/skills/databricks-spark-structured-streaming/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/alessandro9110/Speech-To-Text-With-Databricks

Made for: Claude Code.

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<a href="https://agentmods.dev/skills/alessandro9110/speech-to-text-with-databricks/databricks-spark-structured-streaming"><img src="https://agentmods.dev/badge/skills/alessandro9110/speech-to-text-with-databricks/databricks-spark-structured-streaming.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 636 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.00636
Opus 5.5 $0.00017 $0.00254
Sonnet 5.5 $0.00009 $0.00127
Haiku 4.5 $0.00004 $0.00064

Measured 1mo ago against content hash 035d4ee67e4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

databricks-spark-structured-streaming 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 1mo 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.

.claude/skills/databricks-spark-structured-streaming/SKILL.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Spark Structured Streaming

Production-ready streaming pipelines with Spark Structured Streaming. This skill provides navigation to detailed patterns and best practices.

Quick Start

from pyspark.sql.functions import col, from_json

# Basic Kafka to Delta streaming
df = (spark
    .readStream
    .format("kafka")
    .option("kafka.bootstrap.servers", "broker:9092")
    .option("subscribe", "topic")
    .load()
    .select(from_json(col("value").cast("string"), schema).alias("data"))
    .select("data.*")
)

df.writeStream \
    .format("delta") \
    .outputMode("append") \
    .option("checkpointLocation", "/Volumes/catalog/checkpoints/stream") \
    .trigger(processingTime="30 seconds") \
    .start("/delta/target_table")

Core Patterns

Pattern Description Reference
Kafka Streaming Kafka to Delta, Kafka to Kafka, Real-Time Mode See kafka-streaming.md
Stream Joins Stream-stream joins, stream-static joins See stream-stream-joins.md, stream-static-joins.md
Multi-Sink Writes Write to multiple tables, parallel merges See multi-sink-writes.md
Merge Operations MERGE performance, parallel merges, optimizations See merge-operations.md

Configuration

Topic Description Reference
Checkpoints Checkpoint management and best practices See checkpoint-best-practices.md
Stateful Operations Watermarks, state stores, RocksDB configuration See stateful-operations.md
Trigger & Cost Trigger selection, cost optimization, RTM See trigger-and-cost-optimization.md

Best Practices

Topic Description Reference
Production Checklist Comprehensive best practices See streaming-best-practices.md

Read the full file on GitHub · 66 lines

Files

What ships with it

9 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.

Changes

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.

  1. 1mo ago First seen · 66 lines · 43 tokens per session scan A 035d4ee67e4a

Subscribe to this mod's changes

databricks-spark-structured-streaming is a skill published in the GitHub repository alessandro9110/Speech-To-Text-With-Databricks (4 stars, last pushed 8mo ago), licensed MIT. It adds 43 tokens to every session and 636 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-02.

Analytics and metricsData and AIdatabricksdelta-lakegenerative-ailakehousemachinespeech-to-text
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