AGENT SKILLBY NOWORK-STUDIO
Canonical NotFair workflow
AT A GLANCE
Canonical NotFair workflow is an agent skill for social media. Audit, diagnose, plan, and safely operate connected LinkedIn Ads accounts through the NotFair MCP, with an export-based fallback. 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-linkedin
- SOURCE REPOSITORY
- nowork-studio/notfair-plugin (opens GitHub in a new tab)
- REPO STARS
- SOURCE REPOSITORY
- LICENSE
- MIT
- SKILL.MD SIZE
- 3.6 KB47 LINES
QUICK ANSWER
- WHAT IT IS01
- Audit, diagnose, plan, and safely operate connected LinkedIn Ads accounts through the NotFair MCP, with an export-based fallback. What sets it apart is how it narrows social content into one specific workflow rather than a broad, generic prompt.
- INPUTS02
- Context for social content: your goals, audience, constraints, and any source material the skill asks for.
- OUTPUT03
- A ready-to-use result for social content: 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-linkedinREAD 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 · 6
Canonical NotFair workflow#
Read ../../paid-ads/paid-ads-linkedin/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-linkedin/.
Supporting file: paid-ads/paid-ads-linkedin/SKILL.md#
LinkedIn Ads#
Read ../shared/operating-contract.md and ../shared/measurement-framework.md before acting. Prefer the linkedin_ads_ tools on the universal NotFair MCP; use a supplied export only when no verified connector is available.
Establish access and qualified-demand context#
- Resolve
~~linkedin-adsto the universal connector'slinkedin_ads_tool surface or a verified compatible connector. CalllistConnectedPlatformswhen using NotFair, then confirm the selected account with a harmless account/setup read. Do not infer LinkedIn access from another platform's tools. - If the connector is missing or unauthorized, request re-authorization or a current export and keep the result plan/review-only.
- Define the sales-qualified conversion, CRM feedback loop, account currency, attribution basis, target CPA or pipeline outcome, and complete date window before diagnosing performance.
Keep lead quantity separate from lead quality. Build targeting hypotheses from job function, seniority, company, industry, or account lists only when the business rationale and audience constraints are defensible.
Read and diagnose#
Use runScript for correlated read-only work across campaign groups, campaigns, creatives, and analytics. Prefer a single broad read. Use specialized point tools for individual objects, conversion rules, lead forms, targeting lookup, or lead-form responses.
Interpret the platform correctly:
- Hierarchy is account → campaign group → campaign → creative.
- Money is returned as a major-unit object such as
{ amount: "50", currencyCode: "USD" }, not micros or cents. - Targeting is a whole tree on the campaign. Preserve existing criteria unless the user explicitly approves replacement.
- Campaign type and cost type are immutable after creation.
- Lead-form responses contain personal data. Retrieve only when necessary, minimize exposure in the response, and never copy raw lead PII into unrelated artifacts.
For reviews, report spend, impressions, link CTR, leads, qualified leads, CPA, and downstream pipeline or revenue by a complete equivalent period. Name the likely driver only when the data supports it.
Execute approved changes safely#
Use dedicated write tools, never the read-only script surface. Show the exact object, current and proposed state, currency exposure, expected effect, and rollback first. Use dry-run previews for spend-affecting creates, budgets, bids, and targeting when available.
- Prefer pause/activate over hard deletion; conversion rules and matched audiences may not be deletable through the API.
- Create campaign groups, campaigns, and creatives in draft, then review targeting, budget, conversion association, and creative before activation.
- Use a stable client request ID only to retry the same uncertain create.
- Resolve targeting names to LinkedIn URNs before setting the full targeting tree.
- Hashing and event-shape enforcement belong to the connector. Do not expose raw customer identifiers in the final report.
- Verify the mutation through returned before/after evidence or a fresh read and report any partial failure.
Finish with the confirmed action, quality metric, observation window, and rollback trigger. If operating from an export, mark recommendations ready_for_review, never published.
FAQ
07 QUESTIONS
01What is the Canonical NotFair workflow agent skill?
Audit, diagnose, plan, and safely operate connected LinkedIn Ads accounts through the NotFair MCP, with an export-based fallback. It is listed under social media and 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-linkedin 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-linkedin/SKILL.md, Establish access and qualified-demand context, Read and diagnose and Execute approved changes safely. Read the full text on this page or in plain markdown at /resources/agent-skills/nowork-studio-notfair-plugin--paid-ads-linkedin--1r3i1yy/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-linkedin/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.