altshiftstudio Creativity
This skill uses Distribution-level Sampling to bypass "mode collapse" and surface high-quality, non-obvious ideas (p < 0.10).
State the goal for using this skill, and align the outcome to it.
Creative Workflow
Follow these phases thoroughly. Show your reasoning to the user.
Phase 1: Explore semantic space
Conduct a reasoning-first exploration of the semantic space. Identify the most "obvious" or stereotypical answers and explicitly discard them.
Announce a list of discarded ideas with a super-short rationale.
Phase 2: Generate
Produce a set of diverse responses:
- $k$ (default 5) from the tail of the distribution (p < 0.15)
- $k$ (default 5) from the head of the distribution (p > 0.85)
Use internal chain-of-thought to explore multiple distinct directions before writing outputs. Assign an estimated probability to each.
Phase 3: Review
- Review the generated set against the broader task user is working on.
- Eliminate any ideas that are irrelevant, or lack impact.
Phase 4: Iteration
Decide whether the current set is sufficient:
- Loop: If ideas lack impact or relevance, re-run Phase 1.
- Finalize: If the set is strong, follow the output format.
Output Format
Present the final set of ideas using Markdown tables. Each idea must have its own table with the following structure:
| Idea {n} | Probability: {P} |
|---|---|
| Idea | [Generated response] |
| Impact | [Short text on how impactful it is to the broader goal] |
| Rationale | [Short text on why it is relevant for the broader task] |
Example Output
| Idea 1 | Probability: 0.04 |
|---|---|
| Idea | Silent Onboarding: Replace tutorial pop-ups with environmental cues embedded in the UI itself. |
| Impact | High. Standard onboardings are often skipped. This reframe lets users "learn by doing." |
| Rationale | Most onboarding assumes explicit instruction. This challenges the pattern by treating the interface as a "learning landscape" rather than a "lesson plan." |
Creative Operators
To ensure non-obvious and creative output, optionally use the methods detailed in operators.md.