marketing-council
marketing-council is a Positioning & messaging skill for AI agents, published by coreyhaines31 in the marketingskills repository on GitHub. Skillspace rates marketing-council D (69/100) and it passed the safety scan; a judge model has also reviewed it.
When the user wants multiple expert perspectives on a marketing question — a simulated board of advisors staffed by legendary marketers (Seth Godin, David Ogilvy, Eugene Schwartz, April Dunford, Rory Sutherland, Alex Hormozi, Byron Sharp, and more). Also use when the user mentions 'marketing council,' 'board of advisors,' 'advisory board,' 'what would Seth Godin say,' 'what would Ogilvy think,' 'channel Hormozi,' 'get multiple perspectives,' 'debate this,' 'have the council review,' 'marketing mentors,' or asks how a famous marketer would approach their problem. The council gives each advisor's take through their documented frameworks, surfaces where they disagree, and synthesizes a recommendation. For executing the winning direction, hand off to positioning, offers, copywriting, ads, or the relevant skill.
- Grade
- D
- Quality
- 69 / 100
- Safety
- Passed
- GitHub stars
- 49,936
Placed #1 of 6 in the judged category final for Positioning & messaging.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 91 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #1 of 6 in the judged category final for Positioning & messaging.
- Trigger
90 90 - Instructions
88 88 - Specificity
88 88 - Safety
92 92 - Disclosure
90 90 - Maintenance
82 82
Best progressive disclosure in the group, loading only the seated advisors' dossiers, plus an explicit simulation-labeling and grounding rule and a built-in dissenter requirement so the council cannot just agree with itself.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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