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Speech-To-Text-With-Databricks: Instructions file for GitHub Copilot

.github/instructions/workflow.instructions.md

Speech-To-Text-With-Databricks workflow.instructions.md is an instructions file for GitHub Copilot from alessandro9110/Speech-To-Text-With-Databricks. It costs 86 tokens per session, scanned A, original, MIT.

A set of project rules for a Databricks speech-to-text pipeline, which turns audio into written text and stores it for later analysis, search, or AI use. The rules cover when workflows run, required checks, and production deployment safety.

In plain words
What is it for?
It helps configure pull-request checks, validate Databricks bundles, control production approvals, and keep secrets and workspace addresses out of committed files.
Why use it?
It prevents unrelated file changes from triggering workflows, blocks unsafe production credential use, and requires validation and tests before deployment.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file.

This is alessandro9110/Speech-To-Text-With-Databricks's own configuration. It tells GitHub Copilot 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 86 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/.github/instructions/workflow.instructions.md
Clone the repo
git clone --depth 1 https://github.com/alessandro9110/Speech-To-Text-With-Databricks

Made for: GitHub Copilot.

Wrote 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.

agentmods badge for Speech-To-Text-With-Databricks workflow.instructions.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/alessandro9110/speech-to-text-with-databricks/workflow/github.svg)](https://agentmods.dev/instructions/alessandro9110/speech-to-text-with-databricks/workflow)
Your own site
<a href="https://agentmods.dev/instructions/alessandro9110/speech-to-text-with-databricks/workflow"><img src="https://agentmods.dev/badge/instructions/alessandro9110/speech-to-text-with-databricks/workflow/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.

agentmods 80×15 button for Speech-To-Text-With-Databricks workflow.instructions.md

Your own site · 80×15
<a href="https://agentmods.dev/instructions/alessandro9110/speech-to-text-with-databricks/workflow"><img src="https://agentmods.dev/badge/instructions/alessandro9110/speech-to-text-with-databricks/workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 This file is loaded in full into every session.
When invoked 86 The same file — it is already loaded in full.
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 $0.00086 $0.00086
Opus 5.5 $0.00034 $0.00034
Sonnet 5.5 $0.00017 $0.00017
Haiku 4.5 $0.00009 $0.00009

Measured 1mo ago against content hash 8d64f99ea09a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

Speech-To-Text-With-Databricks workflow.instructions.md 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.

.github/instructions/workflow.instructions.md · 10 lines

What it actually says

  • Workflows must use paths filters to run only on:
    • speech_to_text_asset_bundle/**
    • .github/workflows/**
  • PR workflows must run lint/tests and databricks bundle validate -t dev/prod
  • Deploy to prod must require approvals and never use dev credentials.
  • Never echo secrets or include real workspace URLs in committed files.
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 · 10 lines · 86 tokens per session scan A 8d64f99ea09a

Subscribe to this mod's changes

Speech-To-Text-With-Databricks workflow.instructions.md is an instructions file published in the GitHub repository alessandro9110/Speech-To-Text-With-Databricks (4 stars, last pushed 8mo ago), licensed MIT. It adds 86 tokens to every session, about $0.0003 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.

CI and CDDevOps and cloudSecuritydatabricksdelta-lakegenerative-ailakehousemachinespeech-to-text
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