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Get Started Free →Generate, evaluate, and narrow brand concepts during early ideation including positioning territories, naming candidates, mood directions, and narrative angles. Use this skill whenever the user is in the early phase of brand creation, exploring brand directions, brainstorming names, building moodboards, generating positioning options, or trying to choose between multiple brand directions. Triggers on brand ideation, brand concept, naming, brand name, name candidates, positioning, brand positioni
.claude/skills/rampstackco-brand-ideation/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 27% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 63% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -10% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 204% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 82% | 0% |
Generate and converge on brand directions before committing to identity work. This is upstream of brand-identity (the visual system) and brand-style-guide (the documentation). It is the divergent-then-convergent thinking phase where ideas are cheap and direction matters more than polish.
brand-identity)brand-style-guide)brand-voice)brand-discovery)If the audience is unclear, run brand-discovery first.
Brand ideation moves through four stages. Each stage diverges (generate options) then converges (pick a direction).
A positioning territory is the strategic space the brand occupies. It is not a tagline. It is the answer to "what does this brand stand for that competitors do not?"
Generate 3 to 5 territories using these angles:
For each territory, write:
Names cluster by approach. Generate names across multiple approaches, not just one.
| Approach | Description | Examples | |---|---|---| | Descriptive | Says what it is | "General Electric," "American Airlines" | | Evocative | Suggests a feeling or quality | "Patagonia," "Oasis," "Stripe" | | Founder | Person's name | "Disney," "Ford," "Tesla" | | Acronym | Letters from longer phrase | "IBM," "BMW," "AWS" | | Coined | Made-up word | "Kodak," "Häagen-Dazs," "Asana" | | Metaphor | Borrowed concept | "Apple," "Amazon," "Twitch" | | Compound | Two words combined | "Facebook," "PayPal," "Spotify" | | Suggestive | Hints at function without describing | "Tide," "Slack," "Sprint" (historical; absorbed into T-Mobile in 2020) |
Generate 8 to 15 candidates per direction. Apply naming filters before short-listing:
A short-listable name passes all six. Most names fail at least one. The bar is necessarily high.
Generate visual directions BEFORE designing anything. Each direction should be distinct enough that a designer would produce visibly different work for each.
For each mood direction (typically 2 to 4):
A mood direction is "Editorial sophistication: Warm cream paper backgrounds, classical serifs, archival photography. Think: The New York Times Magazine meets a literary journal."
A bad mood direction is "Modern and clean."
Every brand has a story. The narrative answers: how do we tell people why this exists?
Common narrative shapes:
For each candidate narrative:
references/ideation-output-template.md.Default output is a markdown brief at brand-ideation.md in the project root. Includes:
Optional: a separate naming-explorations.md with the full list of 30 to 50 candidates (the "kill file") in case the chosen finalists fail later checks.
This skill's output depends on data, measurements, or tool results it cannot generate on its own. When a required input, tool, or data source is unavailable or unverifiable, the sanctioned output is the deliverable with the gap stated: what was needed, what was actually obtained or verified, and which parts of the output are affected. Fabricating, estimating, or interpolating a required number to complete the deliverable is never sanctioned. A stated gap is a complete answer.
references/ideation-output-template.md - Fillable template for the ideation deliverable.references/naming-evaluation-rubric.md - The 6-criteria filter applied with examples.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 34,469 | 30,255 | -12% | 1 | 1 | 0% | 5,760 | 6,985 | +21% | 0 | 0 | — |
case-02 | fail→pass | 27,221 | 22,141 | -19% | 1 | 1 | 0% | 4,423 | 5,605 | +27% | 0 | 0 | — |
case-03 | fail→pass | 24,592 | 27,592 | +12% | 1 | 1 | 0% | 3,907 | 6,375 | +63% | 0 | 0 | — |
case-04 | pass→pass | 30,138 | 4,709 | -84% | 1 | 1 | 0% | 6,194 | 2,885 | -53% | 0 | 0 | — |
case-05 | fail→pass | 19,195 | 5,563 | -71% | 1 | 1 | 0% | 3,367 | 3,029 | -10% | 0 | 0 | — |
case-06 | fail→fail | 18,807 | 22,749 | +21% | 1 | 1 | 0% | 2,978 | 5,657 | +90% | 0 | 0 | — |
case-07 | fail→fail | 9,955 | 10,493 | +5% | 1 | 1 | 0% | 1,537 | 3,735 | +143% | 0 | 0 | — |
case-08 | fail→pass | 10,693 | 20,649 | +93% | 1 | 1 | 0% | 1,781 | 5,415 | +204% | 0 | 0 | — |
case-09 | fail→fail | 7,908 | 21,150 | +167% | 1 | 1 | 0% | 1,196 | 5,134 | +329% | 0 | 0 | — |
case-10 | fail→fail | 14,469 | 18,426 | +27% | 1 | 1 | 0% | 2,282 | 5,167 | +126% | 0 | 0 | — |
case-11 | fail→fail | 3,620 | 10,500 | +190% | 1 | 1 | 0% | 572 | 3,563 | +523% | 0 | 0 | — |
case-12 | fail→fail | 5,602 | 4,198 | -25% | 1 | 1 | 0% | 758 | 2,748 | +263% | 0 | 0 | — |
case-13 | fail→pass | 14,918 | 13,735 | -8% | 1 | 1 | 0% | 2,269 | 4,136 | +82% | 0 | 0 | — |
case-14 | pass→pass | 17,042 | 14,463 | -15% | 1 | 1 | 0% | 2,435 | 4,373 | +80% | 0 | 0 | — |
case-15 | pass→pass | 18,753 | 18,737 | -0% | 1 | 1 | 0% | 2,662 | 4,970 | +87% | 0 | 0 | — |
case-16 | pass→pass | 15,700 | 12,771 | -19% | 1 | 1 | 0% | 2,519 | 4,060 | +61% | 0 | 0 | — |
case-17 | pass→pass | 12,201 | 10,377 | -15% | 1 | 1 | 0% | 1,678 | 3,696 | +120% | 0 | 0 | — |
case-18 | fail→pass | 8,833 | 2,468 | -72% | 1 | 1 | 0% | 1,364 | 2,498 | +83% | 0 | 0 | — |
case-19 | fail→pass | 12,333 | 5,673 | -54% | 1 | 1 | 0% | 1,754 | 2,891 | +65% | 0 | 0 | — |
case-20 | pass→pass | 21,007 | 19,213 | -9% | 1 | 1 | 0% | 3,219 | 4,999 | +55% | 0 | 0 | — |
case-21 | fail→pass | 13,193 | 20,054 | +52% | 1 | 1 | 0% | 2,082 | 5,122 | +146% | 0 | 0 | — |
case-22 | pass→pass | 10,761 | 9,807 | -9% | 1 | 1 | 0% | 1,543 | 3,559 | +131% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +36 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.