azure-ai-contentunderstanding-py

azure-ai-contentunderstanding-py is a skill for Claude Code, Codex from benjaminasterA/antigravity-awesome-skills. It costs 0 tokens per session (1,704 once invoked), scanned A, original, MIT.

A Python SDK for extracting meaning from documents, video, audio, and images. It can return structured content for RAG, a method of giving an AI relevant source material before it answers.

In plain words
What is it for?
Use it to analyze files, extract document text or other semantic content, and prepare results for search or AI applications.
Why use it?
It saves you from writing separate extraction code for each media type and prepares content for automated workflows.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to analyze files, extract document text or other semantic content, and prepare results for search or AI applications.

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Install with agentmods
npx agentmods add skills/benjaminastera/antigravity-awesome-skills/azure-ai-contentunderstanding-py
Install

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.

Any agent
npx skills add benjaminasterA/antigravity-awesome-skills --skill azure-ai-contentunderstanding-py
Clone the repo
git clone --depth 1 https://github.com/benjaminasterA/antigravity-awesome-skills

Made for: Claude Code, Codex.

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.

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README.md
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agentmods 80×15 button for azure-ai-contentunderstanding-py

Your own site · 80×15
<a href="https://agentmods.dev/skills/benjaminastera/antigravity-awesome-skills/azure-ai-contentunderstanding-py"><img src="https://agentmods.dev/badge/skills/benjaminastera/antigravity-awesome-skills/azure-ai-contentunderstanding-py.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,704 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00000 $0.01704
Opus 5 $0.00000 $0.00852
Sonnet 5 $0.00000 $0.00341
Haiku 4.5 $0.00000 $0.00170

Measured 8d ago against content hash baac6f757d2d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

azure-ai-contentunderstanding-py 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.

Origin

Copies of this mod

7 near-identical copies found in the catalogue:

skills/azure-ai-contentunderstanding-py/SKILL.md · 279 lines

How it starts

The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Azure AI Content Understanding SDK for Python

Multimodal AI service that extracts semantic content from documents, video, audio, and image files for RAG and automated workflows.

Installation

pip install azure-ai-contentunderstanding

Environment Variables

CONTENTUNDERSTANDING_ENDPOINT=https://<resource>.cognitiveservices.azure.com/

Authentication

import os
from azure.ai.contentunderstanding import ContentUnderstandingClient
from azure.identity import DefaultAzureCredential

endpoint = os.environ["CONTENTUNDERSTANDING_ENDPOINT"]
credential = DefaultAzureCredential()
client = ContentUnderstandingClient(endpoint=endpoint, credential=credential)

Core Workflow

Content Understanding operations are asynchronous long-running operations:

  1. Begin Analysis — Start the analysis operation with begin_analyze() (returns a poller)
  2. Poll for Results — Poll until analysis completes (SDK handles this with .result())
  3. Process Results — Extract structured results from AnalyzeResult.contents

Prebuilt Analyzers

Analyzer Content Type Purpose
prebuilt-documentSearch Documents Extract markdown for RAG applications
prebuilt-imageSearch Images Extract content from images
prebuilt-audioSearch Audio Transcribe audio with timing
prebuilt-videoSearch Video Extract frames, transcripts, summaries
prebuilt-invoice Documents Extract invoice fields

Analyze Document

import os
from azure.ai.contentunderstanding import ContentUnderstandingClient
from azure.ai.contentunderstanding.models import AnalyzeInput
from azure.identity import DefaultAzureCredential

endpoint = os.environ["CONTENTUNDERSTANDING_ENDPOINT"]
client = ContentUnderstandingClient(
    endpoint=endpoint,
    credential=DefaultAzureCredential()
)

# Analyze document from URL
poller = client.begin_analyze(
    analyzer_id="prebuilt-documentSearch",
    inputs=[AnalyzeInput(url="https://example.com/document.pdf")]
)

result = poller.result()

# Access markdown content (contents is a list)
content = result.contents[0]
print(content.markdown)

Read the full file on GitHub · 279 lines

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. 8d ago First seen · 279 lines · 0 tokens per session scan A baac6f757d2d

Subscribe to this mod's changes

azure-ai-contentunderstanding-py is a skill published in the GitHub repository benjaminasterA/antigravity-awesome-skills (271 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,704 tokens. 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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