documentdb-agent-kit GEMINI.md

Configuration instructions for a Gemini CLI extension that manages and tunes Azure DocumentDB deployments. Gemini CLI is a command-line coding assistant, and the extension connects it to the database through configured profiles.

In plain words
What is it for?
Use it to configure local or hosted DocumentDB access for Gemini CLI, sign in through Azure identity, or enable additional tool capabilities beyond read-only access.
Why use it?
It explains how to provide database connection details, prefer Microsoft Entra or OIDC login, and control which tools can make changes.

Instructions file for Gemini CLI

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.

agentmods
npx agentmods add instructions/azure/documentdb-agent-kit/gemini-md
Clone the repo
git clone --depth 1 https://github.com/Azure/documentdb-agent-kit

Made for: Gemini CLI.

Per session 354 This file is loaded in full into every session.
When invoked 354 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
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 $0.00354 $0.00354
Opus 5 $0.00177 $0.00177
Sonnet 5 $0.00071 $0.00071
Haiku 4.5 $0.00035 $0.00035

Measured yesterday against content hash 3e50b68c11e3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

documentdb-agent-kit GEMINI.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 yesterday.

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.

GEMINI.md · 40 lines

What it actually says

Azure DocumentDB Gemini Extension

This extension provides tools for managing and optimizing Azure DocumentDB (MongoDB-compatible) deployments using the official documentdb-mcp-server.

Configuration

The extension requires a connection profile to be configured server-side. Set the DOCUMENTDB_CONNECTION_PROFILES environment variable before launching Gemini CLI.

Recommended: Microsoft Entra / OIDC backend authentication

export DOCUMENTDB_CONNECTION_PROFILES='{"sandbox":{"authMode":"entra","endpoint":"<cluster>.mongocluster.cosmos.azure.com","tokenScope":"https://ossrdbms-aad.database.windows.net/.default","allowedHosts":["*.mongocluster.cosmos.azure.com"]}}'

Sign in with Azure CLI for local development:

az login --tenant <tenant-id>

In Azure hosting, use managed identity or workload identity and grant that identity access to the backend database.

Local / sandbox: SCRAM connection string

export DOCUMENTDB_CONNECTION_PROFILES='{"local":{"uriEnv":"DOCUMENTDB_LOCAL_URI"}}'
export DOCUMENTDB_LOCAL_URI='mongodb://localhost:27017'

Tool capability gates

By default only read tools are enabled. To enable higher-impact tools, override in your shell before launching Gemini:

export ENABLE_WRITE_TOOLS=true        # insert / update / delete / find_and_modify
export ENABLE_MANAGEMENT_TOOLS=true   # drop_database, drop_collection, create_index, ...

If the user needs help configuring the MCP server, use the mcp-setup skill to guide them through the process. For the full list of options, see the DocumentDB MCP Server documentation.

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. yesterday First seen · 40 lines · 354 tokens per session scan A 3e50b68c11e3

Subscribe to this mod's changes

documentdb-agent-kit GEMINI.md is an instructions file published in the GitHub repository Azure/documentdb-agent-kit (5 stars, last pushed 1mo ago), licensed MIT. It adds 354 tokens to every session, about $0.0018 per session on Opus 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 2026-08-31.

Related

Other instructions, from other repositories

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

buildNext

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

next.js AGENTS.md

Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

spec-kit AGENTS.md

Instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,040 tokens

langchain AGENTS.md

Instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,345 tokens