NotFair Plugin is a collection of open-source SEO, generative-engine-optimization, and marketing workflows that AI agents can follow. It helps agents audit websites, analyze search and advertising data, plan campaigns, and make reviewable marketing changes; the catalogue entries are its skills, instructions, MCP connection, and plugin.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nowork-studio/notfair-plugin --skill paid-ads-linkedingit clone --depth 1 https://github.com/nowork-studio/notfair-pluginWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nowork-studio/notfair-plugin/paid-ads-linkedin)<a href="https://agentmods.dev/skills/nowork-studio/notfair-plugin/paid-ads-linkedin"><img src="https://agentmods.dev/badge/skills/nowork-studio/notfair-plugin/paid-ads-linkedin/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nowork-studio/notfair-plugin/paid-ads-linkedin"><img src="https://agentmods.dev/badge/skills/nowork-studio/notfair-plugin/paid-ads-linkedin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.00722 |
| Opus 5 | $0.00036 | $0.00361 |
| Sonnet 5 | $0.00014 | $0.00144 |
| Haiku 4.5 | $0.00007 | $0.00072 |
Grade A, and why
paid-ads-linkedin scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Ads
Read ../shared/operating-contract.md and ../shared/measurement-framework.md before acting. Use live account data from the connected platform; use a supplied export when no verified connector is available.
Establish access and qualified-demand context
- Follow
../../docs/mcp-connection.md. Resolve~~linkedin-adsto 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. - 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
Correlate campaign groups, campaigns, creatives, and analytics as needed. Choose available capabilities for individual objects, conversion rules, lead forms, targeting information, or lead responses; retrieve only what the question needs.
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.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday Changed 6da3bb1927d1
- 13d ago First seen · 45 lines · 72 tokens per session scan A 6be58b7ade00
paid-ads-linkedin is a skill published in the GitHub repository nowork-studio/notfair-plugin (3,740 stars, last pushed yesterday), licensed MIT. It adds 72 tokens to every session and 722 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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elixir-idioms
OTP/BEAM patterns and Elixir idioms — GenServer, Supervisor, Task, Registry, pattern matching, with chains, pipes. Use when designing processes or debugging BEAM issues.
tidewave-integration
Tidewave MCP runtime tools — debugging, smoke testing, live state inspection, SQL queries, hex docs. Use when evaluating code in a running Phoenix app.
security
Enforce Elixir/Phoenix security — auth, OAuth, sessions, CSRF, XSS, SQL injection, input validation, secrets. Use when editing auth files, login flows, RBAC, or API keys.
chief-strategy-officer
Owns where the business plays and how it wins over a multi-year horizon — portfolio choices, corporate development, strategic partnerships, and planning under uncertainty. Use this for a decision about which markets or businesses to be in, whether to build, buy, or partner, how to allocate capital across business…