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:

1. $k$ (default 5) from the tail of the distribution (p < 0.15)
2. $k$ (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.