AGENT SKILLBY NOWORK-STUDIO
Canonical NotFair workflow
AT A GLANCE
Canonical NotFair workflow is a paid ads agent skill from nowork-studio. Produce a read-only, evidence-based paid-media performance review across connected platforms or supplied exports. It is published in the nowork-studio/notfair-plugin GitHub repository (3.4K stars) under the MIT license. Install it with: npx skills add nowork-studio/notfair-plugin --skill paid-ads-review
- SOURCE REPOSITORY
- nowork-studio/notfair-plugin (opens GitHub in a new tab)
- REPO STARS
- SOURCE REPOSITORY
- LICENSE
- MIT
- CATEGORIES
- SKILL.MD SIZE
- 1.9 KB26 LINES
QUICK ANSWER
- WHAT IT IS01
- Produce a read-only, evidence-based paid-media performance review across connected platforms or supplied exports. It stands out by giving paid media a defined shape, so the agent asks for better context and returns a more usable result.
- 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-reviewREAD 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-review/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-review/.
Supporting file: paid-ads/paid-ads-review/SKILL.md#
Paid Ads Review#
Read ../shared/operating-contract.md and ../shared/measurement-framework.md. This is read-only.
Assemble comparable evidence#
Check which sources are actually connected, request the missing export rather than reporting a failed call, and use the most recent complete equivalent window. For every source, keep currency, conversion definition, attribution window, and reporting lag visible. Verify tracking before treating CPA, ROAS, or revenue as a decision-grade metric.
For live platform accounts, hand data collection and diagnostics to /notfair:google-ads, /notfair:meta-ads, /notfair:paid-ads-x, or /notfair:paid-ads-linkedin. Keep TikTok, Amazon, and ChatGPT Ads review grounded in a verified connector or supplied platform export.
Report the decision, not a dashboard transcription#
Lead with the strongest contributor, the largest risk, and one recommended next action. Include a platform scorecard with spend, qualified conversions, CPA, attributable revenue/ROAS where available, link CTR, and pace against the declared budget. Compare each row to the preceding equivalent period and name the likely driver only when data supports it.
Do not present an unqualified blended CPA or ROAS. If a cross-channel aggregate is useful, label the consistent conversion definition, attribution source, spend-weighted formula, and included channels. Separate confirmed facts from inference and mark absent tracking or data as a blocking limitation.
End with hold, investigate, or one proposed action; route mutations to /notfair:paid-ads-optimize or the relevant platform operator skill.
FAQ
07 QUESTIONS
01What is the Canonical NotFair workflow agent skill?
Produce a read-only, evidence-based paid-media performance review across connected platforms or supplied exports. 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-review 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-review/SKILL.md, Assemble comparable evidence and Report the decision, not a dashboard transcription. Read the full text on this page or in plain markdown at /resources/agent-skills/nowork-studio-notfair-plugin--paid-ads-review--1b7fcx8/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-review/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.