comparison-tool-design
The comparison-tool-design skill provides frameworks for building side-by-side comparison tools that drive user decisions through honest axis selection, transparent recommendation logic, and deliberate simplification rather than feature dumps. Use it when scoping new comparison tools, auditing underperforming feature grids, designing recommendation engines that maintain user trust, or determining which attributes deserve prominent placement in plan comparisons, product comparisons, or alternative-evaluation interfaces.
git clone --depth 1 https://github.com/rampstackco/claude-skills /tmp/comparison-tool-design && cp -r /tmp/comparison-tool-design/dist/pi/.agents/skills/comparison-tool-design ~/.claude/skills/comparison-tool-designSKILL.md
# Comparison Tool Design
A senior product marketing director's playbook for designing side-by-side comparison tools that help users decide rather than just listing features. Plan-compare, product-compare, alternative-compare. Axis selection, default-comparison logic, recommendation discipline. The discipline of building a comparison tool that earns the user's trust.
Most comparison tools fail in one of two ways. They dump every feature into a giant grid (4 options × 40 features = 160 cells) and ask the user to weigh everything against everything. The user leaves without choosing. Or they pretend to be neutral comparisons but are actually sales pitches with biased defaults and weighted framing; the user catches the bias and trust collapses.
The comparison tools that work do something different. Genuine like-for-like comparison plus an explicit opinionated recommendation. "For X audience, choose Y." The recommendation is visible, defended, and not the only path; users can override. The tool helps the user decide rather than asking them to decide alone.
The voice is the senior product marketing director who has watched comparison tools double conversion when redesigned with honest recommendations and watched them collapse when feature grids grew without decision support. Practical, opinionated about which axes matter, willing to call out when the comparison is decoration.
When to use this skill: scoping a comparison tool for the first time, auditing a feature-grid comparison that produces no conversion lift, designing recommendation logic that is honest about the recommendation, or deciding which axes earn placement in a comparison tool.
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## What this skill covers
This skill spans side-by-side comparison tools. The growth-tooling distinctions:
- `calculator-design` is calculators that give a number. This skill is comparing known options.
- `quiz-and-assessment-design` is quizzes that give a category. This skill is comparing options the user already knows about.
- **`comparison-tool-design` (this skill)** is axis selection, default-comparison logic, recommendation engine, filter-and-toggle UX.
- `landing-page-copy` is pricing-page copy; one specific application of comparison tools is the pricing page.
- `content-strategy` is upstream; what topics warrant comparison content.
The audience: product marketers, growth marketers, content marketers running vs-pages and decision-support tooling, agencies running comparison work for clients.
Out of scope: calculator design (covered by `calculator-design`); quiz design (covered by `quiz-and-assessment-design`); the engineering implementation; specific Webflow/Framer/CMS configurations (those stay implementation-side).
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## The comparison-tool decision: when comparison tools earn investment
Before designing the tool, decide whether a comparison tool is the right answer.
**Comparison tools earn investment when:**
- The audience is at a decision moment between known options (vs unknown options where a quiz or recommendation tool fits better).
- The options have meaningful differences that warrant side-by-side analysis.
- The brand can articulate honest distinctions between options without becoming sales pitch.
- The audience benefits from decision support, not just feature listing.
**Comparison tools do NOT earn investment when:**
- Options are too similar to compare meaningfully.
- The brand cannot make honest distinctions without creating sales-pitch dynamics.
- A simple comparison table or written content would serve.
- The audience does not actually face this decision (manufactured comparisons).
The decision is not "should we have a comparison tool"; it is "is the comparison tool the right tool for this decision."
Detail in [`references/comparison-tool-decision-criteria.md`](references/comparison-tool-decision-criteria.md).
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## Feature-list-dump vs hidden-recommendation vs honest-comparison-with-guidance
The keystone framing.
**Feature-list-dump.** Every option's every feature in a giant grid. No decision support. The user is asked to weigh 40 cells against each other; most leave without choosing. Cost: design effort wasted on a grid that does not produce decisions; the audience perceives the grid as overwhelming.
**Hidden-recommendation.** "Comparison" tool that is actually a sales pitch. Defaults favor one option; framing weights the answer; the recommendation is invisible but baked in. Trust erodes when users notice the bias. Cost: short-term conversion may look fine; long-term brand damage from "manipulative" reputation.
**Honest-comparison-with-guidance.** Genuine like-for-like comparison plus an explicit opinionated recommendation ("For X audience, choose Y"). The recommendation is visible, defended, and not the only path; users can override. Cost: design effort upfront is significant; conversion typically improves because users feel respected and helped.
The litmus test. Does the tool tell the user what to choose for their specific situation, with reasoning? If yes, honest-comparison-with-guidance. If it dumps features without guidance, feature-list-dump. If it says "the right answer is obviously [our preferred option]" without acknowledgment, hidden-recommendation.
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## Axis selection: which dimensions matter, which are noise
The single most consequential decision in comparison tool design.
**The principle.** Axes (the rows of the comparison) should be the dimensions that genuinely affect the decision, not every feature available.
**Strong axes.**
- **Decision-relevant capabilities.** Features that materially affect the audience's outcome.
- **Cost dimensions.** Price, total cost of ownership, hidden costs.
- **Constraint dimensions.** Capacity, scale, integration support.
- **Service dimensions.** Support quality, onboarding, SLA.
- **Risk dimensions.** Vendor stability, security, compliance.
**Weak axes.**
- **Marketing checkboxes.** Features that exist on every option; checkmarks across the rowRun a comprehensive WCAG accessibility audit covering perceivable, operable, understandable, and robust principles. Use this skill whenever the user wants to audit accessibility, review WCAG compliance, fix accessibility issues, prepare for accessibility certification, address an accessibility lawsuit risk, or systematically improve a site's accessibility. Triggers on accessibility audit, WCAG audit, a11y audit, accessibility compliance, ADA compliance, screen reader test, keyboard navigation, accessibility report, fix accessibility, axe scan. Also triggers when accessibility issues have been reported and need systematic remediation.
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