Adjar Quick Start

This guide connects an ad account to Adjar, exports it as plain-text config, and walks your first change through the full loop — ask, review, apply, measure. It works the same for Google Ads and OpenAI Ads; where a command differs, pick your platform’s tab. The whole process takes about 10 minutes.

Prerequisites

Before you begin, make sure you have:

The adjar CLI installed
An ad account you want to manage, with API access — Google Ads or OpenAI Ads
An AI agent or assistant (Claude Code, Cursor, or any other)

Install the CLI

macOS (Apple silicon + Intel):

curl -fsSL https://adjar.ai/install.sh | bash

This downloads the standalone adjar binary, verifies its checksum, and installs it to ~/.local/bin — no Node or other runtime required.

macOS only for now. Linux and Windows builds are on the way.

Verify the installation:

adjar --version

Set up credentials

Each platform has its own credentials file. Produce yours, then point Adjar at it.

Google Ads
OpenAI Ads

Follow Get Google Ads API access to produce your google.json file, then point Adjar at it:

export ADJAR_CREDENTIALS=/path/to/google.json

Or pass --credentials /path/to/google.json on any command. Your account ID is the customer_id in that file — you’ll pass it to adjar import next.

Follow Get OpenAI Ads API access to produce your openai.json file, then point Adjar at it:

export ADJAR_CREDENTIALS=/path/to/openai.json

Or pass --credentials /path/to/openai.json on any command. Your account ID looks like adacct_… — read it off the OpenAI Ads dashboard or the ad_account endpoint.

The loop: ask, review, apply, measure

Adjar replaces the ad console with a config-driven workflow. Your account lives as plain-text TOML in your repo, your AI agent edits it, and the adjar CLI turns the diff into a reviewable plan it applies only when you approve. The performance report Adjar pulls back becomes your next ask. Import your account once, then run the loop.

Import your account

Export your entire account into local TOML config. Replace <id> with your account ID.

Google Ads
OpenAI Ads

adjar import --account <id> -o config/google.toml

Adjar writes every campaign, ad group, keyword, and creative into config/google.toml as plain text you can version-control.

adjar import --platform openai --account <id> -o config/openai.toml

Adjar writes every campaign, ad group, and ad into config/openai.toml as plain text you can version-control.

Re-run it anytime to refresh the file from the live account.

Large accounts can be split across multiple files with a top-level imports directive. See the config reference for Google Ads or OpenAI Ads.

Commit your config

Add the config to version control. This is the baseline — every future change shows up as a diff against it.

git add config/
git commit -m "chore: initial adjar config export"

Store your config in the same repo as your website or app, so your AI agent already has the context it needs when you ask it to work on ads.

Ask your agent to make a change

Open your AI agent and tell it what you want in plain language. It reads your config, then edits the TOML directly — no special prompt engineering, the format is self-describing.

"Pause every campaign that spent more than $50 this month
 with zero conversions."

● Read config/google.toml
● Edited config/google.toml
   1 campaign status "active" → "paused"

Review the plan

Before anything touches your live account, run adjar plan. Adjar compares your local config against the live account and prints every change as a diff. The platform is read from the config’s platform field, so a single --config is all it needs:

adjar plan --config config/google.toml

The plan shows:

Fields being changed, with old vs. new values
New campaigns, ad groups, keywords, or ads being created
Resources being paused or removed

Nothing is applied until you approve.

Apply the changes

If the plan looks right, apply it:

adjar apply --config config/google.toml

Adjar executes the changes against the platform’s API and writes the assigned IDs back into your config. Commit the result — your repo is now the source of truth:

git add config/
git commit -m "feat: pause overspending campaigns with no conversions"

Every change is a git commit. If an experiment underperforms, rollback is git revert — not a hunt through the console’s change history.

Pull a performance report

Close the loop: adjar report pulls a month of performance as plain-text markdown, written right beside your config. Pass --month for a calendar month, or omit it to default to the last complete month.

Google Ads
OpenAI Ads

adjar report --config config/google.toml --month 2026-05 -o reports/2026-05.google.md

## Campaigns
| Campaign      | Clicks |   CTR |    Cost | Conv. |
| ------------- | -----: | ----: | ------: | ----: |
| Running Shoes |    140 | 2.90% | $182.40 |     6 |
| Trail Shoes   |     86 | 1.74% | $121.10 |     2 |

adjar report --config config/openai.toml --month 2026-05 -o reports/2026-05.openai.md

## Campaigns
| Campaign            | Impr. | Clicks |   CTR |  Spend |
| ------------------- | ----: | -----: | ----: | -----: |
| Database Governance | 8,000 |     40 | 0.50% | $140.00 |

Need a single day instead? Pass --day 2026-05-31. It’s mutually exclusive with --month.

Config and report are both plain text, so next round your agent reads them side by side — spotting what spends without converting before it proposes the next change. Commit it alongside your config, and the next ask starts here.

That’s the full loop — and it repeats. Each round starts from the latest report.

How the pieces fit together

Piece	What it does
TOML config	Declarative representation of your entire ad account
Markdown reports	Performance data your agent can read
`adjar import`	Exports your live account into TOML the first time
`adjar plan`	Compares local config to the live account; prints the diff
`adjar apply`	Executes the diff against the ad platform’s API
`adjar report`	Pulls performance into a Markdown report
Your AI agent	Reads config + reports, proposes edits, explains its reasoning
You	Review every plan, approve what ships, provide judgment

Next steps

CLI Reference

The core workflow plus full flags and options for every command.

Config Reference

Understand every field in your TOML config — Google Ads and OpenAI Ads.

File Organization

How to split config across files and how imports composes them.

adjar report

Pull performance into Markdown that closes the loop.

Get Started

Connect a Platform

CLI Reference

Config Reference

Adjar Quick Start

Prerequisites

Install the CLI

Set up credentials

The loop: ask, review, apply, measure

How the pieces fit together

Next steps

CLI Reference

Config Reference

File Organization

adjar report

​Prerequisites

​Install the CLI

​Set up credentials

​The loop: ask, review, apply, measure

​How the pieces fit together

​Next steps

CLI Reference

Config Reference

File Organization

adjar report

Prerequisites

Install the CLI

Set up credentials

The loop: ask, review, apply, measure

How the pieces fit together

Next steps