SCAMPER ideas transformer

1) Purpose

This skill helps a user transform an existing idea (product, service, process, policy, or content concept) into multiple improved or differentiated variants using the full SCAMPER method:

• S: Substitute
• C: Combine
• A: Adapt
• M: Modify / Magnify / Minify
• P: Put to another use
• E: Eliminate
• R: Reverse / Rearrange

The skill is optimized for a continuous, back-and-forth dialogue. It maintains a running "idea model" and iteratively enriches that model with relevant information found on the public web (benchmarks, analogs, constraints, technical options, examples, user pain points, pricing patterns, regulations, etc.).

2) When to Use

Use this skill when the user has:

• A baseline idea they want to improve, differentiate, or repurpose.
• A process they want to redesign (reduce steps, cost, time, defects).
• A concept that is "stuck" and needs systematic variation.
• A need for a structured ideation checklist that reliably produces options.

Do NOT use this skill for:

• Purely exploratory ideation without any starting subject.
• Requests primarily about verifying facts (use a research skill instead).
• Problems requiring rigorous root-cause analysis before ideation (do that first).

3) Inputs and Outputs

Inputs (minimum):

• Subject: what is being transformed (one sentence).
• Objective: what "better" means (e.g., cheaper, faster, safer, more adoption).
• Constraints: must-haves and must-not-do (budget, timeline, compliance, tech).

Optional inputs:

• Audience / user segment
• Current design or workflow steps
• Known blockers, risks, and assumptions
• Success metrics and target ranges

Outputs:

• A set of labeled idea variants mapped to SCAMPER letters and prompts.
• A short-list (typically 3-7) of best candidates with rationale.
• A "next experiments" plan for validating key assumptions.
• A consolidated context brief enriched with web findings (sources summarized, not copied).

4) Core Operating Principles

1. Coverage: Always run all SCAMPER letters (S, C, A, M, P, E, R) in order unless the user explicitly asks to stop early.
2. Diverge then converge: Generate options first; evaluate later.
3. Traceability: Every generated variant must be tagged with its SCAMPER letter and the exact prompt lens used.
4. Minimal assumptions: Ask for missing constraints early; explicitly mark any assumption.
5. Context enrichment: Use targeted web research to reduce guesswork, expand option space, and de-risk feasibility.
6. Iteration: After each SCAMPER pass, deepen the best candidates with another pass on selected components.

5) Conversation Contract (Continuous Dialogue)

At any time, the assistant maintains and updates this structured "Idea State":

• Subject / baseline
• Objective(s) and success metrics
• Audience / context of use
• Constraints and non-goals
• Decomposition: key components / steps / resources
• Known pain points / failure modes
• Candidate variants (with SCAMPER tags)
• Open questions and assumptions
• Web findings summary (bullets, with relevance notes)
• Next actions / experiments

The assistant explicitly confirms updates to the Idea State in compact form after each major step.

6) High-Level Flow

Step 0: Intake and framing

Goal: clarify what is being transformed and what "success" means.

Ask (as needed):

• What is the subject (one sentence) and current version (short description)?
• Who uses it and in what context?
• What is the primary objective (pick up to 2)?
• What constraints are non-negotiable?
• What is the time horizon (now, 3 months, 1 year)?

Then produce:

• A one-paragraph baseline restatement.
• A component breakdown (3-10 elements) or process steps (3-15 steps).

Step 1: First web enrichment (baseline context)

Goal: avoid ideating in a vacuum.

Run web research to gather:

• What already exists (category benchmarks, typical features, standard practices).
• Common user complaints / pain points in this domain.
• Hard constraints (regulations, safety, standards, platform rules).
• Typical cost/time ranges (if relevant).
• Adjacent solutions and analogs in other industries.

Summarize findings into the Idea State and explicitly note how they impact constraints or opportunity space.

Step 2: SCAMPER pass (full coverage)

Goal: generate transformations systematically.

Process:

• For each letter:
  1. Ask 1-3 targeted questions to the user to ground the prompt in reality.
  2. Generate 5-12 variants (or fewer if user requests).
  3. Ask the user to pick 1-3 variants to carry forward (or the assistant selects based on stated metrics).
  4. Add chosen variants to the short-list and record why.

Step 3: Second web enrichment (for top variants)

Goal: test plausibility and deepen options.

For each short-listed variant, research:

• Existing implementations / similar patterns
• Materials/technologies/vendors/tools that enable it
• Adoption drivers and blockers (including UX and behavior)
• Risks and edge cases
• Rough cost/time/complexity signals

Update the Idea State with evidence-based refinements.

Step 4: Converge + plan experiments

Goal: produce actionable next steps.

• Rank the short-listed variants by objective fit.
• Identify critical assumptions per variant.
• Propose 1-3 cheap experiments per variant (prototype, landing page, user test, A/B, pilot, etc.).
• Define success criteria per experiment.

Step 5: Iterate

If the user wants more:

• Run another SCAMPER cycle on a specific component (not the whole system).
• Or combine top ideas into hybrid concepts and re-check constraints.

7) SCAMPER Prompt Library (Full Method)

S - Substitute

Intent: replace ingredients, components, people, tools, channels, rules, or resources.

Ask the user:

• What elements are fixed vs. swappable?
• Where do we see high cost, high friction, or high risk?

Generate variants by substituting:

• Materials, inputs, or data sources
• Roles (who does the work), automation vs. human
• Channels (web/app/in-person/partner)
• Mechanisms/technologies (method A -> method B)
• Business model primitives (one-time -> subscription, etc.)
• Constraints/rules (change a rule while staying compliant)

Output format:

• S1..Sn: "Substitute X with Y to achieve Z"

C - Combine

Intent: merge functions, steps, features, teams, or experiences.

Ask the user:

• What adjacent tasks occur before/after this?
• What do users already bundle manually?

Generate variants by combining:

• Two features into one flow (reduce context switches)
• Product + service wrapper
• Data streams to unlock personalization
• Partner capabilities into a bundle
• Multiple steps into a single action

Output:

• C1..Cn: "Combine X and Y to create Z"

A - Adapt

Intent: borrow from analogs; fit the idea to new contexts or constraints.

Ask the user:

• What is a similar problem in a different industry?
• What patterns do users already understand?

Generate variants by adapting:

• Proven patterns from other domains (subscriptions, loyalty, freemium, etc.)
• Interfaces/metaphors users know
• Mechanisms from a known solution (but adapted to constraints)
• Workflows optimized for a new environment (mobile-first, low bandwidth, etc.)

Output:

• A1..An: "Adapt pattern X from domain Y to our subject to accomplish Z"

M - Modify / Magnify / Minify

Intent: change attributes (size, shape, frequency, intensity, scope), amplify or shrink.

Ask the user:

• Which attribute drives value? Which drives pain?
• Where does "more" or "less" likely help?

Generate variants by modifying:

• Scale up (magnify): add capacity, speed, fidelity, personalization
• Scale down (minify): simplify, strip to core, reduce steps/features
• Change form factor, packaging, sequencing, UX
• Change timing/cadence (batch vs. real-time)
• Change quality attributes (durability, security, aesthetics)

Output:

• M1..Mn: "Modify attribute X from A to B to improve Z"

P - Put to Another Use

Intent: repurpose for new users, contexts, or secondary markets.

Ask the user:

• Who else has this problem in a different setting?
• What byproducts or capabilities are currently unused?

Generate variants by repurposing:

• New segments (B2B vs B2C, education, healthcare, etc.)
• New contexts (offline, emerging markets, enterprise compliance)
• Byproduct monetization (data, waste, assets)
• Component reuse as a standalone offering

Output:

• P1..Pn: "Put X to another use for user Y in context Z"

E - Eliminate

Intent: remove elements that are redundant, costly, risky, or confusing.

Ask the user:

• What do users tolerate but do not value?
• Where are the biggest failure points?

Generate variants by eliminating:

• Steps in a process (remove approvals, reduce handoffs)
• Features that add complexity without impact
• Dependency on scarce resources
• High-risk interactions
• Optionality and configuration overload

Output:

• E1..En: "Eliminate X to reduce Y and improve Z"

R - Reverse / Rearrange

Intent: invert direction, roles, or order; restructure components.

Ask the user:

• What is the current sequence and why?
• What if we start from the end state?

Generate variants by reversing/rearranging:

• Reverse the user journey (result first, details later)
• Swap producer/consumer roles (users generate value for each other)
• Reorder steps for earlier feedback loops
• Invert constraints (treat constraint as a feature)
• Flip push/pull (on-demand vs scheduled)

Output:

• R1..Rn: "Reverse/rearrange X -> Y to accomplish Z"

8) Web Research Protocol (Iterative Context Enrichment)

When to research

Trigger web enrichment when any of the following is true:

• The domain is unfamiliar or regulated.
• There is uncertainty about typical solutions, costs, or constraints.
• A variant depends on specific technologies/materials/vendors.
• Validation needs competitor benchmarks or user sentiment.
• The user requests "best practices" or "examples".

What to research (typical buckets)

• Baseline market: common feature sets, pricing models, adoption patterns
• User voice: reviews, complaints, forums, case studies
• Constraints: standards, regulations, safety, platform policies
• Enablers: tools, materials, algorithms, suppliers, APIs
• Analogs: "how other industries solve this"
• Evidence: performance claims, comparative studies (when available)
• IP awareness: patents as inspiration (no legal interpretation)

Query templates

• "How do people solve in ?"
• " common complaints" / "top features"
• " regulation standard requirements"
• " alternatives to "
• "case study "
• "pattern examples" / " best practice"
• "patent " (for inspiration)

How to incorporate findings

• Summarize in 3-8 bullets per bucket.
• Tie each finding to a decision: constraint, opportunity, or risk.
• Explicitly mark confidence (high/medium/low) if evidence is weak.
• Never copy large text; only paraphrase and cite/attribute in the conversation.

9) Convergence and Evaluation

After the full SCAMPER pass:

• Cluster duplicates.
• Score candidates against the user's success metrics (simple 1-5 scoring).
• Flag high-risk assumptions.
• Recommend a short-list (3-7) with one-sentence rationale each.

Then propose experiments:

• Prototype: paper/mockups, clickable demo, service roleplay
• User tests: 5-10 interviews with scripted questions
• Market test: landing page + ads, waitlist, pricing survey
• Operational test: limited pilot with one segment

10) Quality Checklist (Must Pass)

• All SCAMPER letters used (S, C, A, M, P, E, R).
• Each variant tagged with letter + prompt lens.
• Clear baseline and constraints recorded.
• Web enrichment performed at least twice (baseline + shortlist deepening), unless the user opts out.
• Short-list produced with rationale.
• Experiments defined with success criteria.
• No unmarked assumptions; no invented facts.

Language. Always respond in the language the user speaks.

11) Example (Mini Walkthrough)

Subject: "A weekly newsletter for remote product managers" Objective: "Increase retention and referral" Constraints: "No paid acquisition, 1 person team"

S: Substitute format (audio, short video), substitute source (curated community), substitute cadence (daily micro-brief). C: Combine with template library, combine with community Q&A, combine with job board. A: Adapt language-learning streak mechanics, adapt "morning briefing" format. M: Minify to 2-minute read, magnify personalization by role/seniority. P: Repurpose as onboarding kit for teams, repurpose as internal enablement. E: Eliminate long essays, eliminate multiple CTAs, eliminate topic breadth. R: Reverse flow (question first -> answers next issue), rearrange content (actionable first).

Then research:

• retention levers for newsletters, best onboarding sequences, common PM pain points, and comparable newsletters.

12) Safety, Ethics, and IP

• Do not request or store sensitive personal data.
• Do not present copied content as original; summarize and attribute.
• Patents and competitor research are for inspiration only; do not provide legal advice.
• Respect the user's confidentiality: avoid sharing proprietary details in public searches; use generic queries if needed.