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Skillzwave

running-marketing-campaigns

3 stars
100
A

Plans, creates, and optimizes digital marketing campaigns including content strategy, social media, email marketing, SEO, and AI visibility (GEO). Generates UTM parameters and tracking URLs. Helps develop go-to-market strategies, campaign messaging, content calendars, and performance measurement frameworks. Use when asked to "create a marketing campaign", "plan content strategy", "build email sequences", "set up UTM tracking", "analyze marketing metrics", "launch a product", "optimize for SEO...

#plan content#references#campaign#SEO#agentic-skill#email#brand#brand voice
Also in: ci cd

Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security

Installation for Agentic Skill

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skilz install SpillwaveSolutions/running-marketing-campaigns-agent-skill/running-marketing-campaigns
skilz install SpillwaveSolutions/running-marketing-campaigns-agent-skill/running-marketing-campaigns --agent opencode
skilz install SpillwaveSolutions/running-marketing-campaigns-agent-skill/running-marketing-campaigns --agent codex
skilz install SpillwaveSolutions/running-marketing-campaigns-agent-skill/running-marketing-campaigns --agent gemini

First time? Install Skilz: pip install skilz

Works with 14 AI coding assistants

Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...

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Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/SpillwaveSolutions/running-marketing-campaigns-agent-skill
2. Copy the agent skill directory:
cp -r running-marketing-campaigns-agent-skill ~/.claude/skills/
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Need detailed installation help? Check our platform-specific guides:

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Agentic Skill Details

Owner
SpillwaveSolutions (GitHub)
Repository
running-marketing-campaigns-agent-skill
Stars
3
Type
Technical
Meta-Domain
productivity
Primary Domain
email
Market Score
100
Agentic Skill Grades →

Agent Skill Grade

A
Score: 100/100 Click to see breakdown

Score Breakdown

Spec Compliance
15/15
PDA Architecture
28/30
Ease of Use
24/25
Writing Style
9/10
Utility
19/20
Modifiers: +7

Areas to Improve

  • Minor verbosity in reference files
  • Scripts section could be more prominent

Recommendations

  • Add trigger phrases to description for discoverability
  • Add table of contents for files over 100 lines

Graded: 2026-01-19

Developer Feedback

I took a look at your running-marketing-campaigns skill and wanted to share some thoughts.

Links:

The TL;DR

You're at 100/100, A grade — this is solid work. The evaluation is based on Anthropic's best practices across five pillars. Your strongest area is Spec Compliance (15/15) — you nailed the technical requirements. Progressive Disclosure Architecture is nearly perfect at 28/30, and Ease of Use hit 24/25.

What's Working Well

  • Spec compliance is perfect — your YAML frontmatter, name conventions, and metadata are exactly right. Clean, no friction.
  • Reference structure is smart — 9 reference files plus 2 Python scripts give you excellent layering. The Domain Reference Guide table that tells users when to load what is chef's kiss for discoverability.
  • Trigger phrases are comprehensive — you've got 12+ specific entry points (UTM, GEO, E-E-A-T, content calendar, brand voice, etc.). This matters for findability across agents.
  • Actionable templates — the copy-paste UTM templates, email sequences, and positioning statements give users immediate value. That's what separates "nice guide" from "actually useful."

The Big One: Verbosity in Reference Files

Your reference files are slightly over-explained in places. Specifically, email-marketing.md's welcome sequence section expands examples that could be consolidated into a single annotated template with a brief variations list. Same pattern shows up in a couple other references.

Why this matters: You lose points on writing style (9/10 vs potential 10/10), but more importantly, users might get fatigued scrolling past ...

AI-Detected Topics

Extracted using NLP analysis

plan content references campaign SEO agentic-skill email brand brand voice marketing content

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