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-optimizegit 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-optimize)<a href="https://agentmods.dev/skills/nowork-studio/notfair-plugin/paid-ads-optimize"><img src="https://agentmods.dev/badge/skills/nowork-studio/notfair-plugin/paid-ads-optimize/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-optimize"><img src="https://agentmods.dev/badge/skills/nowork-studio/notfair-plugin/paid-ads-optimize.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 | $0.00054 | $0.00414 |
| Opus 5 | $0.00027 | $0.00207 |
| Sonnet 5 | $0.00011 | $0.00083 |
| Haiku 4.5 | $0.00005 | $0.00041 |
Grade A, and why
paid-ads-optimize 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 9d ago.
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.
What it actually says
Paid Ads Optimization
Read ../shared/operating-contract.md and ../shared/measurement-framework.md. Review before changing anything.
Diagnose before cutting
Verify the conversion signal, period completeness, spend volume, attribution model, and recent account changes. Spend with no recorded conversion can indicate broken tracking or immature data; treat it as a hypothesis until the signal and volume support an intervention. Check landing-page or operational failures before blaming targeting.
Classify the bottleneck as query/audience quality, creative fatigue, delivery/rank, budget constraint, landing-page mismatch, tracking, or economics. Use the specialized Google, Meta, X, or LinkedIn skill for live diagnosis. For other platforms, analyze only the supplied or verified data.
Rank reversible moves
Prefer this order: exclude an irrelevant query, placement, or audience; pause the narrowest losing unit; adjust budget or bid in a measured step; then consider structural change. For a reallocation, show the current and proposed allocations, the same total budget unless the user approves an increase, and the observable hypothesis.
Do not declare a loser from a few clicks. Set a threshold appropriate to the named target CPA, conversion lag, and channel role. Preserve upper-funnel and assisted-conversion context rather than judging all campaigns on last-click CPA alone.
Approval and follow-up
Present each exact mutation with scope, current value, proposed value, currency exposure, rationale, and review date. After approval, execute only through the verified platform skill or connector, read back the result, and record the intervention's expected effect and guardrail. Revisit after the declared observation window instead of promising a generic ongoing watch.
What ships with it
1 file 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.
- 9d ago First seen · 26 lines · 54 tokens per session scan A 93af4458502c
paid-ads-optimize is a skill published in the GitHub repository nowork-studio/notfair-plugin (3,662 stars, last pushed 3d ago), licensed MIT. It adds 54 tokens to every session and 414 once invoked, about $0.0003 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.
Other skills, from other repositories
octowiz
Octowiz AI coding workflow coordinator. Reads IntegraHub memory doctrine at runtime, detects where you are in the development lifecycle, and routes to the right skill combination from superpowers + mattpocock-skills. Use this skill at the START of any development work — whether you have a fresh idea, an existing plan…
setup
Setup orchestrator for the Octowiz Bridge. Re-runs the live environment check, builds a gap list, and runs only the phases needed: plugins, memory, repo, verify. Invoked automatically by octowiz:octowiz when hard gaps are detected.
build-user-persona
Build evidence-backed user personas from research inputs. Creates structured persona documents grounded in evidence, with each attribute clearly labeled as research-validated or inferred. Use this skill when you need personas for an FR, strategy doc, or design brief. Trigger on: "build a persona", "create user…
competitive-analysis
Structure a competitive landscape analysis — player profiles, capability comparison matrix, whitespace opportunities, and strategic implications. Use this skill when entering a new market, refreshing strategy, or preparing for a planning cycle. Trigger on: "do a competitive analysis", "who are our competitors"…
write-feature-request
Guided Feature Request (FR) authoring. Assists the user in writing a high-quality FR by collecting structured inputs (problem, solution, outcomes, requirements), then auto-generates Acceptance Criteria for every requirement. If any AC cannot be written due to missing information, the skill identifies the gaps and…
write-product-strategy
Generate comprehensive product strategy documents aligned with business goals. Use this when defining or updating your product's strategic direction, aligning teams on where to play and how to win, or creating a STRATEGY.md that bridges vision and execution. Triggers include: clarifying product strategy, articulating…