azure-ai-contentunderstanding-py

azure-ai-contentunderstanding-py is a skill for Claude Code from 26BB/agentic-awesome-skills-mcp. It costs 32 tokens per session (1,730 once invoked), scanned A, a copy of azure-ai-contentunderstanding-py, MIT.

A Python toolkit for extracting meaning from documents, images, audio, and video with Azure AI. It can produce structured content, including text suitable for RAG, a method for retrieving source information before generating an answer.

In plain words
What is it for?
Use it to analyze files, extract structured results, create searchable document content, and prepare multimodal data for RAG systems.
Why use it?
It removes the need to build separate extraction workflows for different file types and prepares content for search or automated processing.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the agentic-awesome-skills plugin — 196 skills shipped together

Good fit Use it to analyze files, extract structured results, create searchable document content, and prepare multimodal data for RAG systems.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/26bb/agentic-awesome-skills-mcp/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 26BB/agentic-awesome-skills-mcp --skill azure-ai-contentunderstanding-py
Clone the repo
git clone --depth 1 https://github.com/26BB/agentic-awesome-skills-mcp

Made for: Claude Code.

Or install agentic-awesome-skills, the plugin that ships this one along with the rest of its 196 skills.

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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Your own site
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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 azure-ai-contentunderstanding-py

Your own site · 80×15
<a href="https://agentmods.dev/skills/26bb/agentic-awesome-skills-mcp/azure-ai-contentunderstanding-py"><img src="https://agentmods.dev/badge/skills/26bb/agentic-awesome-skills-mcp/azure-ai-contentunderstanding-py.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,730 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 94% copy Near-identical to another mod 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 $0.00032 $0.01730
Opus 5 $0.00016 $0.00865
Sonnet 5 $0.00006 $0.00346
Haiku 4.5 $0.00003 $0.00173

Measured 8d ago against content hash 3a3078229519, 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

This is a copy

94% identical to azure-ai-contentunderstanding-py — 13 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.

plugins/agentic-awesome-skills-claude/skills/azure-ai-contentunderstanding-py/SKILL.md · 282 lines

How it starts

The opening of the file, as written. The whole thing — 282 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 · 282 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 · 282 lines · 32 tokens per session scan A 3a3078229519

Subscribe to this mod's changes

azure-ai-contentunderstanding-py is a skill published in the GitHub repository 26BB/agentic-awesome-skills-mcp (1 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 1,730 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to azure-ai-contentunderstanding-py, differing in 13 lines, and is treated as a copy.

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