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parallel-concepts — Claude Code skill: several solutions at once

Builds several genuinely different solutions to one problem while each still costs a sketch instead of a build.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add Owl-Listener/designer-skills --skill parallel-concepts -a claude-code
Open on GitHub

What parallel-concepts does

The skill takes a problem that already has a proposed solution and constructs a set of other solutions to the same problem, held at equal effort until evidence shows which one wins. It decides how wide the set should be and which dimension the concepts must differ on. Ranking and cutting are left to concept-selection.

Distinctness is behavioural, not visual: does the user do something different? Concepts get spread across sequence, unit of interaction (one item, a batch, a stream), division of labour between person and system, entry point, and commitment point. Two concepts with the same steps in the same order and different styling are one concept rendered twice.

The cost is honest: n concepts cost roughly n times as much. So the skill advises spreading early, while a concept is still a sketch rather than a build. Keep the visual language constant across the set, or the variable under test stops being isolated. And do not carry a concept you would refuse to build.

What it helps with

  • spread one problem into several different solutions before committing
  • find which assumptions in a design are load-bearing and which are arbitrary
  • strip the first idea of the advantage it got from arriving first
  • collect feedback about the options instead of a verdict on the designer
  • compare concepts held at comparable fidelity

Example prompts for the agent

  • Build three parallel concepts for new-user onboarding that differ on entry point
  • Give me a set of checkout concepts: one item at a time, a batch, and a stream
  • Spread these concepts by commitment point and keep the visual language constant

How to install parallel-concepts

1Skills CLI (Vercel)

npx skills add Owl-Listener/designer-skills --skill parallel-concepts -a claude-code

2Manually: put the files in place

~/.claude/skills/parallel-concepts/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/parallel-concepts/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about parallel-concepts

How do I install parallel-concepts in Claude?

Run npx skills add Owl-Listener/designer-skills --skill parallel-concepts -a claude-code. The skill lands at ~/.claude/skills/parallel-concepts/SKILL.md.

What does parallel-concepts do?

It builds several different solutions to the same problem and holds them at equal effort until there is evidence to choose. They differ in what the user does, not in how they look.

How is parallel-concepts different from concept-selection?

parallel-concepts only builds the set and does not rank it. Choosing between the finished concepts is the job of concept-selection.

Source text

SKILL.md · MIT
---
name: parallel-concepts
description: Build several genuinely different solutions to the same problem at once, spread across what the user does rather than how it looks. Use when one direction is on the table and the team is about to refine it by default. For choosing between the concepts afterwards, use `concept-selection`.
---
# Parallel Concepts
You are an expert in divergent exploration — holding multiple competing solutions to one problem before committing to any of them.
## What You Do
You take a problem that already has a proposed solution and construct a set of genuinely different solutions to the same problem, held at equal effort until there is evidence to choose. You decide how wide the set should be and which dimension the concepts must differ on. You do not rank or eliminate them — that is `concept-selection`.
## Why Parallel Beats Serial
Iteration and exploration buy different things. Refining one concept improves that concept. Building several in parallel improves your model of the solution space — you learn which of your assumptions were load-bearing and which were arbitrary.
Stanford's parallel prototyping research (Dow, Glienke and Klemmer, 2010) found designers who produced concepts in parallel outperformed those who iterated serially on a single design for the same total effort, measured on real audience response rather than preference. Two secondary effects matter as much as the result:
- **Critique lands better.** With one design on the table, feedback reads as a verdict on the designer. With several, it reads as information about the options.
- **The first idea loses its unearned advantage.** Whatever arrives first becomes the reference point, and every later idea gets judged as a deviation from it rather than on its own terms. A parallel set removes the incumbent.
The cost is real — n concepts cost roughly n times as much. The resolution is to spread early, while a concept still costs a sketch instead of a build.
## What Makes Concepts Distinct
A set is only informative if its members differ on the dimension the decision turns on. The test is behavioural, not visual: **does the user do something different?**
- **Sequence** — what the user is asked for first, and what waits
- **Unit of interaction** — one item at a time, a batch, or a continuous stream
- **Division of labour** — what the person decides versus what the system decides for them
- **Entry point** — where the task begins and what it assumes the user already knows
- **Commitment point** — how far in the user goes before the action becomes irreversible
Two concepts with the same steps in the same order and different visual treatment are one concept rendered twice. Cut one and spend the effort on a real third direction.
## Sizing the Set
The count is a consequence of cost and stakes, not a target to hit:
- Three cheap sketches beat two polished mockups at the same total effort
- Concepts must sit at **comparable fidelity** — a rendered option beats a rough one on presentation alone, whatever their merits
- If you cannot say what a concept tests that the others do not, it is padding — drop it
## Best Practices
- Write the question the set has to answer before drawing anything; a set that answers no question is a portfolio, not an exploration
- Give every concept enough effort to be defensible — a deliberately weak option is a strawman and corrupts the comparison
- Hold the visual language constant across the set so the variable under test stays isolated
- Do not carry a concept you would refuse to build; an option nobody would ship is not an option
- Not for choosing which problem to solve — that is `opportunity-framework` (ux-strategy)

© Owl-Listener · MIT · Owl-Listener/designer-skills

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