Owl-Listener

Critique a screen's brand consistency against mood.md, voice.md, and tokens.md.

Critique a screen's composition — balance, whitespace, rhythm, and gestalt principles.

Critique a screen's typography — scale usage, readability, consistency, and token compliance.

Critique a screen's visual hierarchy — entry point, eye flow, weight distribution, and emphasis.

Identify, categorize, and prioritize accumulated design inconsistencies and structural problems across a product.

Communicate design's contribution to business and user outcomes in terms that resonate with stakeholders.

Build and maintain a research repository that makes findings findable, reusable, and cumulative across the organization.

Design surveys that collect reliable, unbiased quantitative data to validate hypotheses and measure user attitudes at scale.

Generate an accessibility decision handoff for engineering. Chains: decision-documentation, compliance-mapping, accessibility-testing-strategy. Use when a design is ready for implementation and the engineering team needs clear accessibility specifications.

Review and surface undocumented accessibility assumptions in an existing feature or product. Chains: decision-documentation, tradeoff-analysis, compliance-mapping, accessibility-debt-tracking. Use when inheriting a product, joining a team, or auditing a feature where accessibility decisions were never formally captured.

Document accessibility decisions and tradeoffs for a feature. Chains: decision-documentation, tradeoff-analysis, compliance-mapping. Use when a feature is being designed or shipped and accessibility decisions need to be captured.

Plan what to test, how to test, and who should test for accessibility. Use when defining a testing approach, planning QA, setting up automated and manual testing, or deciding what level of accessibility testing a project needs. Triggers on: accessibility testing, how to test, test plan, automated testing, manual testing, screen reader testing, user testing, accessibility QA, what to test, testing strategy.

Track and manage accessibility debt — known accessibility issues that have been deferred. Use when managing a backlog of accessibility issues, planning remediation, or when accessibility problems are accumulating faster than they're being fixed. Triggers on: accessibility debt, tech debt, known issues, backlog, deferred, we'll fix it later, remediation, accessibility backlog, accumulating issues, regression.

Communicate accessibility decisions, requirements, and value to stakeholders who aren't accessibility specialists. Use when presenting accessibility work to leadership, product managers, engineers, or anyone who needs to understand why accessibility decisions matter. Triggers on: stakeholder, business case, justify accessibility, explain accessibility, leadership, executive, ROI, why accessibility, cost of accessibility, persuade, convince, accessibility presentation.

Map design decisions to accessibility standards and legal requirements. Use when documenting WCAG conformance, preparing for audits, tracking compliance status, or when legal or procurement requires accessibility documentation. Triggers on: WCAG, compliance, conformance, audit, VPAT, accessibility statement, legal requirement, ADA, EAA, European Accessibility Act, Section 508, EN 301 549, accessibility standard, success criterion.

Analyse accessibility tradeoffs when a design decision improves accessibility for one group but may affect another, or when accessibility competes with other requirements. Use when facing conflicting accessibility needs, business pressure to reduce accessibility scope, or technical constraints that limit accessibility options. Triggers on: tradeoff, trade-off, compromise, accessibility vs performance, accessibility vs deadline, conflicting needs, which users, who do we prioritise, can't do both, accessibility scope.

MUST run before any other Designpowers skill — shows welcome, checks taste profile, and routes to the correct first skill. Triggers on ANY design-related message. No other Designpowers skill may run until the welcome sequence has completed

You MUST use this before any creative or design work — building features, creating components, designing interfaces, modifying user-facing behaviour. Explores intent, constraints, users, and context before any design decisions are made

Use when starting a new project or when taste decisions are made — accumulates the user's aesthetic preferences, recurring patterns, and design instincts across projects so each new project starts with what the system already knows about their taste

Use when any Designpowers agent starts work or completes work — maintains the shared design state file that all agents read from and write to. Invoke to initialise, read, or update the living design state document

Use when setting design direction — establishing principles, competitive positioning, experience mapping, or aligning stakeholders on what the design should achieve and why

Use when calibrating aesthetic direction — capturing design references, quality benchmarks, and the subjective qualities that make a design feel elevated. Invoked between strategy and design to give agents a shared sense of what "good" looks and feels like for this project

Use after the fix round to validate the design by walking through key tasks as each persona — simulating how Jordan (low-vision), Priya (non-native speaker), Marcus (motor impairment), or any project persona would actually experience the interface. Catches the issues that code review misses because they only surface in the act of using

Use before declaring any design work complete, fixed, or ready — requires running verification and confirming output before making any success claims. Evidence before assertions, always

Proactively identifying failure modes, misuse, and unintended consequences.

Managing shared context, memory, and state across multiple agents.

Coordinating text, image, voice, and tool-use modalities in a single interaction.

Helping users form warranted trust in the AI — neither overtrust nor undertrust — through deliberate confidence and source signalling.

Reading user emotional state from text signals — caps, punctuation density, repetition, latency — and adapting before the user disengages.