AGENT SKILLBY NOWORK-STUDIO
Canonical NotFair workflow
AT A GLANCE
Canonical NotFair workflow is an agent skill for paid ads. Plan and review ChatGPT Ads experiments without assuming ad inventory, account access, or platform capabilities. The nowork-studio/notfair-plugin repository on GitHub, maintained by nowork-studio, has 3.4K stars and the MIT license. To add it, run npx skills add nowork-studio/notfair-plugin --skill paid-ads-chatgpt
- SOURCE REPOSITORY
- nowork-studio/notfair-plugin (opens GitHub in a new tab)
- REPO STARS
- SOURCE REPOSITORY
- LICENSE
- MIT
- CATEGORIES
- SKILL.MD SIZE
- 1.7 KB22 LINES
QUICK ANSWER
- WHAT IT IS01
- Plan and review ChatGPT Ads experiments without assuming ad inventory, account access, or platform capabilities. Its edge is a particular angle on paid media, giving the agent tighter constraints than a plain canonical NotFair workflow request.
- INPUTS02
- Context for paid media: your goals, audience, constraints, and any source material the skill asks for.
- OUTPUT03
- A ready-to-use result for paid media: the analysis, copy, or recommendations the agent produces.
INSTALL
One command adds this skill from its source repository.
npx skills add nowork-studio/notfair-plugin --skill paid-ads-chatgptREAD THE SKILL.MD BELOW BEFORE YOU RUN IT. SKILLS INSTRUCT YOUR AGENT.
SKILL.MD
The full file, as published in the source repository. Copy it, download it or open it on GitHub.
ON THIS PAGE · 5
Canonical NotFair workflow#
Read ../../paid-ads/paid-ads-chatgpt/SKILL.md (opens in a new tab) completely, then follow it as the active workflow. Resolve every relative reference from that file against ../../paid-ads/paid-ads-chatgpt/.
Supporting file: paid-ads/paid-ads-chatgpt/SKILL.md#
ChatGPT Ads Planning#
Read ../shared/operating-contract.md and ../shared/measurement-framework.md. This plugin has no declared first-party NotFair ChatGPT Ads connector. Do not claim that inventory, campaign creation, targeting, or creative formats are currently available without official, current evidence.
Design a bounded experiment#
Define the business objective, approved destination, conversion event, source-of-truth measurement, geographic and audience constraints, spend ceiling, and observation window. Write a concise, concrete message that earns attention without claiming results the business cannot substantiate. Include a claim ledger, rights review, and an explicit policy/eligibility check owned by the human platform operator.
Present a ready_for_review test brief with: hypothesis, audience/context assumptions, creative and landing-page message match, budget and monthly maximum, primary metric, guardrail, attribution caveat, and stop condition. Treat early delivery or engagement as directional signal, not proof of incremental conversions.
Verify externally#
If the user provides an official account export or a verified connector becomes available, review only what it exposes and preserve its attribution definition. Otherwise, provide the brief and state the exact missing access. Never fabricate a campaign ID, delivery result, or platform setting.
FAQ
07 QUESTIONS
01What is the Canonical NotFair workflow agent skill?
Plan and review ChatGPT Ads experiments without assuming ad inventory, account access, or platform capabilities. It is listed under paid ads in the 100xLab agent skills directory.
02How do I install Canonical NotFair workflow in Cursor, Claude Code, or Codex?
Run npx skills add nowork-studio/notfair-plugin --skill paid-ads-chatgpt in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only Canonical NotFair workflow, not every skill in the repository.
03What does the Canonical NotFair workflow SKILL.md cover?
The SKILL.md includes sections on Supporting file: paid-ads/paid-ads-chatgpt/SKILL.md, Design a bounded experiment and Verify externally. Read the full text on this page or in plain markdown at /resources/agent-skills/nowork-studio-notfair-plugin--paid-ads-chatgpt--1vin10v/raw.
04Which agents can use Canonical NotFair workflow?
Canonical NotFair workflow installs with the cross-agent skills installer (npx skills add), which sets it up for agents such as Claude Code, Cursor and Codex. Each agent loads the SKILL.md when you ask for the skill by name.
05What license is Canonical NotFair workflow under?
The nowork-studio/notfair-plugin repository declares the MIT license. Read the license file in the repository before you copy or redistribute the skill.
06Is Canonical NotFair workflow free to use?
Reading, copying and installing Canonical NotFair workflow costs nothing: it is published in a public GitHub repository under the MIT license. Reuse and redistribution follow that license.
07Where is the source of Canonical NotFair workflow?
Canonical NotFair workflow comes from https://github.com/nowork-studio/notfair-plugin, which has 3.4K GitHub stars. The SKILL.md is at https://github.com/nowork-studio/notfair-plugin/blob/HEAD/skills/paid-ads-chatgpt/SKILL.md. The author is nowork-studio.
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ATTRIBUTION
Canonical NotFair workflow was written by its original authors and is published in nowork-studio/notfair-plugin (opens GitHub in a new tab) under the MIT license. All rights stay with the original authors.
100xLab did not write, maintain or endorse this skill. This page lists it for discovery. Repo stars belong to the source repository, not to the skill. Review any skill before you install it.