Paid Ads X

OrganizationPopular

nowork-studio

paid-ads-x

Audit, diagnose, and safely operate connected X Ads (Twitter Ads) accounts through the NotFair MCP. Use for X Ads performance, campaign or line-item analysis, spend, conversions, targeting, promoted posts, audiences, budgets, bids, creative, campaign setup, or approved X Ads changes.

Overview

Publisher	nowork-studio
Repository	`notfair-plugin`
Skill name	`paid-ads-x`
Stars	3.8K
Forks	488
Bundled files	2
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by nowork-studio on GitHub. Read the source before you install it.

Installation

Install the Paid Ads X AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/nowork-studio/notfair-plugin.git /tmp/notfair-plugin
mkdir -p .claude/skills
cp -r /tmp/notfair-plugin/paid-ads/paid-ads-x .claude/skills/paid-ads-x

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Paid Ads X in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Paid Ads X on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Paid Ads X is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

X Ads

Read ../shared/operating-contract.md and ../shared/measurement-framework.md before acting. Use the live account data from the connected platform as the source of truth.

Establish the live scope

Follow ../../docs/mcp-connection.md. Resolve ~~x-ads to the live connection. Use its current instructions and capability descriptions to choose tools, and verify the requested platform and account from live data. Do not infer access from another connected platform.
Confirm the selected account with a harmless account/setup read. If the connector is missing or unauthorized, direct the user to connect or re-authorize X Ads and stop before claiming live access.
Record the account currency, timezone, objective, conversion definition, attribution basis, and requested date window. Treat tracking gaps as limitations, not zero performance.

Diagnose with one broad read

Pull the campaigns, line items, funding/configuration, and performance relevant to the question. Choose available read capabilities and batch related data when useful.

Interpret the platform correctly:

Hierarchy is account → funding instrument → campaign → line item → promoted post/account.
Money fields ending in *_local_micro are local-currency major units multiplied by 1,000,000. Divide by 1,000,000 before displaying or comparing them.
A line item's primary_web_event_tag describes its optimization configuration. It does not prove that attributed conversions are zero; read conversion metrics from performance data.
Synchronous stats are suited to short, unsegmented windows. Use the connector's long-window performance read when the requested window or breakdown exceeds the script surface's current limits.
Compare complete equivalent periods and name spend, impressions, engagement/link CTR, conversions, CPA or ROAS only when the returned fields support them.

Lead with the business decision: strongest contributor, largest material risk, likely cause supported by data, and the smallest useful next action. Separate measured facts from inference.

Execute approved changes safely

Use a supported write capability and respect its current contract. Show the exact account, entity, current value, proposed value, spend exposure, risk, and rollback before acting. Prefer a dry-run preview for budget, bid, targeting, optimization-event, and create operations when the connector offers it.

Prefer pause/enable over irreversible deletion.
Create campaigns and line items paused, then verify configuration before activation.
Reuse the same client request ID only when retrying the same create after an uncertain response; use a new ID for a genuinely new entity.
Treat optimization-event changes as learning resets and say so before approval.
Resolve targeting names to platform IDs before applying criteria; preserve unrelated targeting unless the user approved a full replacement.
After an approved mutation, use the returned before/after evidence or a fresh read to confirm the resulting state. Report partial failures plainly.

Finish with the confirmed action, observation window, success metric, and rollback trigger. A proposal remains ready_for_review; call it published only after the live connector confirms it.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

agents/openai.yaml1 KB
evals/evals.json2 KB

Frequently asked questions

What does the Paid Ads X AI skill do?

Why use Paid Ads X on TypingMind?

Because you install it once and use it with any model. Paid Ads X is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Paid Ads X in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nowork-studio/notfair-plugin/tree/main/paid-ads/paid-ads-x. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Paid Ads X?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Paid Ads X?

As many as you like. As long as a model supports skills, you can use Paid Ads X with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Paid Ads X AI skill free?

Yes. It is published on GitHub by nowork-studio under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

X Ads

Establish the live scope

Diagnose with one broad read

Execute approved changes safely

Bundled files

Frequently asked questions

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