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 nicepkg/ai-workflow --skill running-marketing-campaignsgit clone --depth 1 https://github.com/nicepkg/ai-workflowWrote 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/nicepkg/ai-workflow/running-marketing-campaigns)<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/running-marketing-campaigns"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/running-marketing-campaigns/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/nicepkg/ai-workflow/running-marketing-campaigns"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/running-marketing-campaigns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00148 | $0.02548 |
| Opus 5 | $0.00074 | $0.01274 |
| Sonnet 5 | $0.00030 | $0.00510 |
| Haiku 4.5 | $0.00015 | $0.00255 |
Grade A, and why
running-marketing-campaigns 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Campaign Execution
Plan, execute, and measure digital marketing campaigns across content, social, email, and analytics.
Contents
- Quick Start
- Domain Reference Guide
- Scripts
- Workflow Decision Tree
- Multi-Domain Queries
- Campaign Validation Checklist
- Persona Adaptation
- Boundaries
Quick Start
Generate UTM Parameters
Source: where traffic originates (google, facebook, newsletter)
Medium: how it arrives (cpc, email, social, organic)
Campaign: initiative name (spring-sale-2025, product-launch)
Format: lowercase, hyphens, no spaces
Input: "Spring Sale 2025" → Output: "spring-sale-2025"
Input: "Q1 Launch Campaign" → Output: "q1-launch-campaign"
Example: ?utm_source=linkedin&utm_medium=social&utm_campaign=q1-launch
Create Email Sequence
- Welcome (immediate): Set expectations, deliver promised value
- Value (day 2-3): Best content or quick win
- Engagement (day 5-7): Encourage reply or action
- Offer (day 10): Clear CTA with incentive
Plan Content Calendar
Essential fields: Title, Target keyword, Funnel stage (TOFU/MOFU/BOFU), Format, Owner, Publish date, Distribution channels.
Check Campaign Performance
Primary metrics by channel:
- Email: Open rate (43% avg), CTR (2% avg), Conversion rate
- Social: Engagement rate, Reach, Click-through
- Paid: ROAS, CPA, CTR
- Content: Traffic, Time on page, Conversions
Domain Reference Guide
| Need | Reference | When to Load |
|---|---|---|
| Plan content strategy | content-strategy.md | Topic clusters, calendars, funnel mapping, repurposing |
| Execute social media | social-media.md | Platform tactics, posting times, engagement benchmarks |
| Build email campaigns | email-marketing.md | Sequences, subject lines, segmentation, deliverability |
| Track campaigns | utm-tracking.md | UTM formatting, naming conventions, GA4 alignment |
| Measure performance | analytics-measurement.md | KPIs, GA4 setup, attribution, ROI calculations |
| Launch products | gtm-tools.md | GTM frameworks, positioning, tool selection |
| Define brand voice | brand-guidelines.md | Voice dimensions, tone, messaging framework, terminology |
| Optimize for search | seo-optimization.md | Technical SEO, on-page, content SEO, link building, E-E-A-T |
| Optimize for AI | geo-optimization.md | GEO, LLMO, AEO, AI Overviews, chatbot visibility |
What ships with it
12 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.
- LICENSE 1.0 KB
- references/analytics-measurement.md 9.5 KB
- references/brand-guidelines.md 16 KB
- references/content-strategy.md 11 KB
- references/email-marketing.md 11 KB
- references/geo-optimization.md 21 KB
- references/gtm-tools.md 11 KB
- references/seo-optimization.md 19 KB
- references/social-media.md 16 KB
- references/utm-tracking.md 7.9 KB
- scripts/brand_checker.py 25 KB runs code
- scripts/utm_tools.py 26 KB runs code
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.
- 6d ago First seen · 286 lines · 148 tokens per session scan A c27c237ff1fd
running-marketing-campaigns is a skill published in the GitHub repository nicepkg/ai-workflow (283 stars, last pushed 7mo ago), licensed MIT. It adds 148 tokens to every session and 2,548 once invoked, about $0.0007 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 2026-09-03.
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