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ad-campaign-analyzer
ad-campaign-analyzer is an open-source data skill for Claude Code and compatible agents, published by sickn33. Its author describes it as: “Analyze cross-channel campaign data, quantify uncertainty, and propose evidence-labeled budget tests without overstating causality.”. The project has 45k stars on GitHub and is available under the MIT license. Add it to your setup with `/plugin marketplace add sickn33/agentic-awesome-skills`.
Installation
Add ad-campaign-analyzer to your agent with:
/plugin marketplace add sickn33/agentic-awesome-skills Always review a skill's source before installing it. This command comes from the skill's public repository; the linked repo is the source of truth for exact setup steps.
When to use it
Reach for ad-campaign-analyzer when you want data help from your agent without writing the same instructions every session. Load the skill and the agent picks it up automatically for relevant tasks.
Strengths
- Clear MIT license — safe to read and adapt
- Ships in sickn33/agentic-awesome-skills, an established project with 44,549 GitHub stars
- Actively maintained (recent commits)
Topics
Frequently asked questions
- What does ad-campaign-analyzer do?
- Analyze cross-channel campaign data, quantify uncertainty, and propose evidence-labeled budget tests without overstating causality.
- How do I install ad-campaign-analyzer?
- Run /plugin marketplace add sickn33/agentic-awesome-skills in your agent, then reload your skills. Review the source at https://github.com/sickn33/agentic-awesome-skills before installing.
- Is ad-campaign-analyzer free to use?
- Yes. ad-campaign-analyzer is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
- Where does ad-campaign-analyzer come from?
- ad-campaign-analyzer ships inside sickn33/agentic-awesome-skills, a repository that contains 62 catalogued skills in total. The repository's 44,549 GitHub stars apply to that whole collection, not to this skill on its own.
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Expert data processing specialist with intelligent DuckDB/Polars selection for maximum performance. Always includes numpy, never uses pandas, runs everything through uv. Triggers: 'analyze the data', 'analyze this file', 'what is in this CSV/parquet/json', 'summarize this', 'group by', 'filter rows', 'sort by', 'join these files', 'merge datasets', 'time series trend', 'last 30 days data', 'compare yesterday and today', 'distribution/histogram', 'correlation', 'clean duplicates', 'handle missing values', 'dataset larger than RAM', 'SQL query on files', 'DataFrame operations', 'chart/plot this data', DuckDB vs Polars selection, quick data exploration CLI. NOT for plain text/code inspection, configs, or tiny inline math.