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Break out of a locked problem frame by picking one disciplined move — reframe, provocation (Po), random stimulus, SCAMPER, inversion, structured analogy, constraint play, or family traversal — and committing to it before evaluating. Use when stuck, when options feel narrow or obvious, when iterations produce variations of the same idea, or when the user says "widen this", "break out of", "think differently", "I'm stuck", "feels too obvious", "stress-test the framing", "what am I missing", or holds two related examples and asks what lies between or beyond them. Complements challenging (which evaluates) and convening-experts (which synthesizes viewpoints); this skill generates distance, not judgment.

Use this Skill: https://skilld.dev/gh/oaustegard/claude-skills/generative-thinking

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README.md

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generative-thinking

Break out of a locked problem frame by picking one disciplined generative move — reframe, provocation (Po), random stimulus, SCAMPER, inversion, structured analogy, constraint play, or family traversal — and committing to it before evaluating.

The skill is the interrupt for fixation, not a brainstorming workshop. Pick one move matched to the diagnosis, run it, over-generate and tail-sift (write next to each candidate the probability the old frame would have reached it; drop the likely ones), apply the fire test (could this output have been produced without the move?), stop.

See SKILL.md for the diagnostic table, per-technique recipes with success signals, LLM-specific sourcing notes, and canonical references. references/stimulus-vocabulary.md is a 128-noun deck for the hashed random stimulus.

Provenance

  • Lateral thinking, Po, random stimulus — Edward de Bono, Lateral Thinking (1970), Serious Creativity (1992)
  • SCAMPER — Bob Eberle (1971), built on Alex Osborn's Applied Imagination (1953)
  • Oblique Strategies — Brian Eno & Peter Schmidt (1974–2001)
  • Functional fixedness (the bias this skill counters) — Karl Duncker (1935/1945); candle problem
  • LLM-specific design fixation — Wadinambiarachchi et al., CHI 2024 (doi:10.1145/3613904.3642919): AI-generated examples during ideation increase fixation and reduce fluency, variety, originality vs. no-support baseline. Motivates the LLM-sourcing section.
  • Family traversal — Balestriero, Pesenti & LeCun, arXiv:2110.09485 (interior ≠ novelty; limits extrapolate, mixtures average)
  • Tail sift (typicality bias, verbalized-probability prompting) — Jiayi Zhang, Simon Yu, Derek Chong, Anthony Sicilia, Michael R. Tomz, Christopher D. Manning & Weiyan Shi, Verbalized Sampling, arXiv:2510.01171
  • Hashed internal random stimulus — Kou Misaki & Takuya Akiba (Sakana AI), String Seed of Thought, arXiv:2510.21150
  • Structured analogy — Andrew Shen, Shaul Druckmann & James Zou (Stanford), Unlocking LLM Creativity in Science through Analogical Reasoning, arXiv:2605.11258, built on Dedre Gentner's structure-mapping theory (Cognitive Science, 1983)

The three 2025–2026 papers were pointed out by Stuart Gray; 0.3.0 is the result.

Complements

  • challenging — evaluates after generation
  • convening-experts — synthesizes multiple role-based viewpoints
  • tiling-tree — exhaustive MECE partitioning of a solution space

This skill generates distance, not judgment, coverage, or consensus.

Source: SKILL.md on GitHub

1 warning4mo3 checks · Risk SAFE
  • Gen Agent Trust Hub4mo

    This skill provides cognitive frameworks and instructional prompts for problem-solving and lateral thinking. It contains no executable code, remote dependencies, or instructions for performing network or file system operations.

  • Socket4mo

    No alerts

  • Snyk4mo

    Risk: MEDIUM · 1 issue

Signed by skilld at 2f31f89. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 2 weeks ago
metadata
{
  "version": "0.3.0"
}

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