Cosmosdb Best Practices
microsoft/vscode-cosmosdb
Azure Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, and SDK usage.
Azure Tables SDK for Python (Storage and Cosmos DB). An agent skill from microsoft/skills.
$ npx skills add microsoft/skills --skill azure-data-tables-py -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install microsoft/skills azure-data-tables-py --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-data-tables-py .claude/skills/azure-data-tables-py && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "azure-data-tables-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-data-tables-py into .claude/skills/azure-data-tables-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-data-tables-py", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-data-tables-pyType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add microsoft/skills --skill azure-data-tables-py -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install microsoft/skills azure-data-tables-py --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-data-tables-py .agents/skills/azure-data-tables-py && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "azure-data-tables-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-data-tables-py into .agents/skills/azure-data-tables-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-data-tables-py", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft/skills --skill azure-data-tables-py -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install microsoft/skills azure-data-tables-py --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-data-tables-py .cursor/skills/azure-data-tables-py && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "azure-data-tables-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-data-tables-py into .cursor/skills/azure-data-tables-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-data-tables-py", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/microsoft/skills.git --path .github/plugins/azure-sdk-python/skills/azure-data-tables-py--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add microsoft/skills --skill azure-data-tables-py -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install microsoft/skills azure-data-tables-py --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-data-tables-py .gemini/skills/azure-data-tables-py && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "azure-data-tables-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-data-tables-py into .gemini/skills/azure-data-tables-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-data-tables-py", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install microsoft/skills azure-data-tables-pyInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add microsoft/skills --skill azure-data-tables-py -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-data-tables-py .github/skills/azure-data-tables-py && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "azure-data-tables-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-data-tables-py into .github/skills/azure-data-tables-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-data-tables-py", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft/skills --skill azure-data-tables-py -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install microsoft/skills azure-data-tables-py --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-data-tables-py .opencode/skills/azure-data-tables-py && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "azure-data-tables-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-data-tables-py into .opencode/skills/azure-data-tables-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-data-tables-py", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
azure-data-tables-pyAzure Tables SDK for Python (Storage and Cosmos DB). An agent skill from microsoft/skills.
Azure Data Tables Py is an agent skill from microsoft/skills, published by the product's own GitHub organization. Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations. Triggers: "table storage", "TableServiceClient", "TableClient", "entities", "PartitionKey", "RowKey".
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/capabilities.md` and `references/non-hero-scenarios.md`).
It sits in Databases, covering NoSQL databases. It works with Microsoft Azure, Python, Azure Cosmos DB and Visual Studio Code. The repository describes itself as: Skills, MCP servers, Custom Agents, Agents.md for SDKs to ground Coding Agents. The licence is MIT.
10 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 354361d. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
pipFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
learn.microsoft.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
AZURE_TOKEN_CREDENTIALSFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Azure Data Tables Py loads about 2.1k tokens when it runs, and up to ~2.9k if it reads all its reference files. Until then it costs about 61 tokens; SKILL.md has 377 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from microsoft/skills at commit 354361d, republished under its MIT licence (© microsoft). 377 words, ~2,103 tokens.
.claude/skills/azure-data-tables-py/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.NoSQL key-value store for structured data (Azure Storage Tables or Cosmos DB Table API).
pip install azure-data-tables azure-identity# Azure Storage Tables
AZURE_STORAGE_ACCOUNT_URL=https://<account>.table.core.windows.net # Required for Azure Storage Tables
# Cosmos DB Table API
COSMOS_TABLE_ENDPOINT=https://<account>.table.cosmos.azure.com # Required for Cosmos DB Table API
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production🔑 Two rules apply to every code sample below:
- Prefer
DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.
- Local dev:
DefaultAzureCredentialworks as-is.- Production: set
AZURE_TOKEN_CREDENTIALS=prod(orAZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.- Wrap every client in a context manager so HTTP transports, sockets, and token caches are released deterministically:
- Sync:
with <Client>(...) as client:- Async:
async with <Client>(...) as client:andasync with DefaultAzureCredential() as credential:(fromazure.identity.aio)Snippets may abbreviate this setup, but production code should always follow both rules.
import os
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.data.tables import TableServiceClient, TableClient
# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
endpoint = "https://<account>.table.core.windows.net"
# Service client (manage tables)
with TableServiceClient(endpoint=endpoint, credential=credential) as service_client:
# Use service_client here (see following sections for operations)
...
# Table client (work with entities)
with TableClient(endpoint=endpoint, table_name="mytable", credential=credential) as table_client:
# Use table_client here (see following sections for operations)
...| Client | Purpose |
|---|---|
TableServiceClient | Create/delete tables, list tables |
TableClient | Entity CRUD, queries |
# 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")Important: Every entity requires PartitionKey and RowKey (together form unique ID).
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 by key (fastest)
entity = table_client.get_entity(
partition_key="sales",
row_key="order-001"
)
print(f"Product: {entity['product']}")# Replace entire entity
entity["quantity"] = 10
table_client.update_entity(entity=entity, mode="replace")
# Merge (update specific fields only)
update = {
"PartitionKey": "sales",
"RowKey": "order-001",
"shipped": True
}
table_client.update_entity(entity=update, mode="merge")table_client.delete_entity(
partition_key="sales",
row_key="order-001"
)# Query by partition (efficient)
entities = table_client.query_entities(
query_filter="PartitionKey eq 'sales'"
)
for entity in entities:
print(entity)# Filter by properties
entities = table_client.query_entities(
query_filter="PartitionKey eq 'sales' and quantity gt 3"
)
# With parameters (safer)
entities = table_client.query_entities(
query_filter="PartitionKey eq @pk and price lt @max_price",
parameters={"pk": "sales", "max_price": 50.0}
)entities = table_client.query_entities(
query_filter="PartitionKey eq 'sales'",
select=["RowKey", "product", "price"]
)# List all (cross-partition - use sparingly)
for entity in table_client.list_entities():
print(entity)from azure.data.tables import TableTransactionError
# Batch operations (same partition only!)
operations = [
("create", {"PartitionKey": "batch", "RowKey": "1", "data": "first"}),
("create", {"PartitionKey": "batch", "RowKey": "2", "data": "second"}),
("upsert", {"PartitionKey": "batch", "RowKey": "3", "data": "third"}),
]
try:
table_client.submit_transaction(operations)
except TableTransactionError as e:
print(f"Transaction failed: {e}")from azure.data.tables.aio import TableServiceClient, TableClient
from azure.identity.aio import DefaultAzureCredential
async def table_operations():
async with DefaultAzureCredential() as credential:
async with TableClient(
endpoint="https://<account>.table.core.windows.net",
table_name="mytable",
credential=credential
) as client:
# Create
await client.create_entity(entity={
"PartitionKey": "async",
"RowKey": "1",
"data": "test"
})
# Query
async for entity in client.query_entities("PartitionKey eq 'async'"):
print(entity)
import asyncio
asyncio.run(table_operations())| Python Type | Table Storage Type |
|---|---|
str | String |
int | Int64 |
float | Double |
bool | Boolean |
datetime | DateTime |
bytes | Binary |
UUID | Guid |
azure.data.tables sync clients with azure.data.tables.aio async clients in the same call path. Choose one mode per module.with TableClient(...) as client: (sync) or async with TableClient(...) as client: (async). For async DefaultAzureCredential from azure.identity.aio, also use async with credential: so tokens and transports are cleaned up.DefaultAzureCredential for portable auth across local dev and Azure (avoid connection strings / API keys when possible).upsert_entity for idempotent writes| File | Contents |
|---|---|
| references/capabilities.md | Additional non-hero capabilities, operation-group coverage, and production checklists. |
| references/non-hero-scenarios.md | Dedicated non-hero examples for secondary/advanced scenarios. |
© microsoft, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 2 other files (references) in .github/plugins/azure-sdk-python/skills/azure-data-tables-py of microsoft/skills.
Open the folder on GitHubat commit 354361d
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in microsoft/skills, which our catalogue first saw on October 7, 2026.
Azure Data Tables Py next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Azure Data Tables Py this skillmicrosoft/skills | 3.1k | 1 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Cosmosdb Best Practicesmicrosoft/vscode-cosmosdb | 200 | — | ~4.3k | Automated safety check: Pass | MIT | |
| Azure Data Tables Pyaiskillstore/marketplace | 430 | 5 repos | ~1.5k | Automated safety check: Pass | None | |
| Azure Storagemicrosoft/GitHub-Copilot-for-Azure | 255 | 2 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Azure Cosmosdbalinaqi/maggy | 707 | 1 repos | ~4.5k | Automated safety check: Pass | MIT | |
| Telemetry Best Practicesmicrosoft/vscode-cosmosdb | 200 | — | ~3.6k | Automated safety check: Pass | MIT |
microsoft/vscode-cosmosdb
Azure Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, and SDK usage.
aiskillstore/marketplace
Azure Tables SDK for Python (Storage and Cosmos DB). An agent skill from aiskillstore/marketplace.
microsoft/GitHub-Copilot-for-Azure
Azure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake.
alinaqi/maggy
Azure Cosmos DB partition keys, consistency levels, change feed, SDK patterns
microsoft/vscode-cosmosdb
Reviews and authors telemetry code in this extension. An agent skill from microsoft/vscode-cosmosdb.
microsoft/vscode-cosmosdb
Generate, explain, edit, and fix Azure Cosmos DB for NoSQL (SQL API) queries.
microsoft/skills
Reference for building on Microsoft Foundry with the azure-ai-projects Python SDK: project clients, versioned agents, evaluations, connections, datasets and indexes.
microsoft/skills
Python guidance for the Azure AI Search SDK covering vector, hybrid and semantic search, index management and indexers, with Entra ID authentication preferred over keys.
microsoft/skills
Covers producer, consumer, and checkpoint-store setup for Azure Event Hubs streaming in Python, with Entra ID auth and partition targeting.
microsoft/skills
Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants.
microsoft/skills
Captures and filters Windows user-mode and kernel debug output from the command line with the Sysinternals DebugView CLI, including bounded runs suited to agents.
microsoft/skills
Build dark-themed React applications using Tailwind CSS with custom theming, glassmorphism effects, and Framer Motion animations.
Categories
Azure Tables SDK for Python (Storage and Cosmos DB). An agent skill from microsoft/skills. Azure Data Tables Py is an agent skill from microsoft/skills, published by the product's own GitHub organization. Azure Tables SDK for Python (Storage and Cosmos DB).
Azure Data Tables Py fits situations like: noSQL key-value storage; batch operations.
Run `npx skills add microsoft/skills --skill azure-data-tables-py -a claude-code`. Or copy the skill folder (.github/plugins/azure-sdk-python/skills/azure-data-tables-py in microsoft/skills) into .claude/skills/azure-data-tables-py in your project. Claude Code loads it when a task matches its description.
Run `npx skills add microsoft/skills --skill azure-data-tables-py -a codex`. Or copy the skill folder (.github/plugins/azure-sdk-python/skills/azure-data-tables-py in microsoft/skills) into .agents/skills/azure-data-tables-py in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/skills --skill azure-data-tables-py -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-data-tables-py, .gemini/skills/azure-data-tables-py, .github/skills/azure-data-tables-py and .opencode/skills/azure-data-tables-py in your project.
Going by SKILL.md and its folder, Azure Data Tables Py needs the command-line tools its instructions call (pip) and credentials named AZURE_TOKEN_CREDENTIALS. Our summary lists: Python 3.
SKILL.md names 1 domain. In commands or code: learn.microsoft.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Azure Data Tables Py is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.1k tokens (SKILL.md is roughly 8.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 786 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Azure Data Tables Py: Cosmosdb Best Practices (microsoft/vscode-cosmosdb, 200 stars), Azure Data Tables Py (aiskillstore/marketplace, 430 stars), Azure Storage (microsoft/GitHub-Copilot-for-Azure, 255 stars) and Azure Cosmosdb (alinaqi/maggy, 707 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
microsoft (a GitHub organization, an official publisher) maintains it in microsoft/skills, which has 3,091 GitHub stars. The repository holds 150 skills in this directory. The repository was last updated on October 6, 2026.
Source: microsoft/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.