azure-data-tables-py

azure-data-tables-py is a skill for Claude Code from Ghosteken/agent-harness. It costs 33 tokens per session (1,395 once invoked), scanned A, a copy of azure-data-tables-py, MIT.

A Python library for storing structured records as simple key-value entities in Azure Storage Tables or the Table API of Cosmos DB, Microsoft's NoSQL database service. It supports creating tables, reading and changing records, queries, and batch operations.

In plain words
What is it for?
Use it for lightweight application data such as user settings, lookup records, device state, or other entities addressed by partition and row keys.
Why use it?
It provides the code needed to work with these Azure table stores without writing the storage protocol yourself. This is useful when your data does not need the fixed structure of a relational database.

Skill for Claude Code

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

Part of the agent-harness plugin — 173 skills, 11 commands, 12 agents shipped together

Good fit Use it for lightweight application data such as user settings, lookup records, device state, or other entities addressed by partition and row keys.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ghosteken/agent-harness/azure-data-tables-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 Ghosteken/agent-harness --skill azure-data-tables-py
Clone the repo
git clone --depth 1 https://github.com/Ghosteken/agent-harness

Made for: Claude Code.

Or install agent-harness, the plugin that ships this one along with the rest of its 173 skills, 11 commands, 12 agents.

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 azure-data-tables-py

README.md
[![agentmods](https://agentmods.dev/badge/skills/ghosteken/agent-harness/azure-data-tables-py/github.svg)](https://agentmods.dev/skills/ghosteken/agent-harness/azure-data-tables-py)
Your own site
<a href="https://agentmods.dev/skills/ghosteken/agent-harness/azure-data-tables-py"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/azure-data-tables-py/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 azure-data-tables-py

Your own site · 80×15
<a href="https://agentmods.dev/skills/ghosteken/agent-harness/azure-data-tables-py"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/azure-data-tables-py.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,395 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 78% 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 $0.00033 $0.01395
Opus 5 $0.00016 $0.00698
Sonnet 5 $0.00007 $0.00279
Haiku 4.5 $0.00003 $0.00139

Measured 7d ago against content hash 4ee24ac24f9d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

azure-data-tables-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 7d 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

78% identical to azure-data-tables-py — 11 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.

archive/skills-community/azure-data-tables-py/SKILL.md · 252 lines

How it starts

The opening of the file, as written. The whole thing — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Azure Tables SDK for Python

NoSQL key-value store for structured data (Azure Storage Tables or Cosmos DB Table API).

Installation

pip install azure-data-tables azure-identity

Environment Variables

# Azure Storage Tables
AZURE_STORAGE_ACCOUNT_URL=https://<account>.table.core.windows.net

# Cosmos DB Table API
COSMOS_TABLE_ENDPOINT=https://<account>.table.cosmos.azure.com

Authentication

from azure.identity import DefaultAzureCredential
from azure.data.tables import TableServiceClient, TableClient

credential = DefaultAzureCredential()
endpoint = "https://<account>.table.core.windows.net"

# Service client (manage tables)
service_client = TableServiceClient(endpoint=endpoint, credential=credential)

# Table client (work with entities)
table_client = TableClient(endpoint=endpoint, table_name="mytable", credential=credential)

Client Types

Client Purpose
TableServiceClient Create/delete tables, list tables
TableClient Entity CRUD, queries

Table Operations

# Create table
service_client.create_table("mytable")

# Create if not exists
service_client.create_table_if_not_exists("mytable")

# Delete table
service_client.delete_table("mytable")

# List tables
for table in service_client.list_tables():
    print(table.name)

# Get table client
table_client = service_client.get_table_client("mytable")

Entity Operations

Important: Every entity requires PartitionKey and RowKey (together form unique ID).

Create Entity

entity = {
    "PartitionKey": "sales",
    "RowKey": "order-001",
    "product": "Widget",
    "quantity": 5,
    "price": 9.99,
    "shipped": False
}

# Create (fails if exists)
table_client.create_entity(entity=entity)

# Upsert (create or replace)
table_client.upsert_entity(entity=entity)

Get Entity

# Get by key (fastest)
entity = table_client.get_entity(
    partition_key="sales",
    row_key="order-001"
)
print(f"Product: {entity['product']}")

Read the full file on GitHub · 252 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. 7d ago First seen · 252 lines · 33 tokens per session scan A 4ee24ac24f9d

Subscribe to this mod's changes

azure-data-tables-py is a skill published in the GitHub repository Ghosteken/agent-harness (2 stars, last pushed 6d ago), licensed MIT. It adds 33 tokens to every session and 1,395 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 78% identical to azure-data-tables-py, differing in 11 lines, and is treated as a copy.