Source profileQuality 91/100

aryaniyaps/lamina/brand/templates/SKILL.md

lamina

Product design skill for developers who build with AI coding agents. Use when you need to know what to build before prompting your agent — domain model, workflows, edge cases, product states, and UX gaps handled upfront. Works alongside Cursor, Claude Code, Codex, Gemini, Pi. Any stack, any UI library. Do NOT use for visual styling, pixel layouts, or writing app source.

Source repository stars
111
Declared platforms
3
Static risk flags
0
Last source update
2026-08-04
Source checked
2026-08-04

Decision brief

What it does—and where it fits

Lamina runs alongside your AI coding agent — Cursor, Claude Code, Codex, Gemini, Pi. It helps you know what to build before you prompt: edge cases, UX gaps, product states, and invariants in a transactional product graph your agent implements. Verified with isolated Persona Miss…

Best for

  • New features where domain rules, user behavior, and system invariants all matter
  • Multi-step flows (onboarding, checkout, settings, wizards)
  • Permission-sensitive or multi-actor interactions

Not for

  • Do NOT use for visual styling, pixel layouts, or writing app source.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexDeclaredSource recordInstall path and trigger
Claude CodeDeclaredSource recordInstall path and trigger
CursorDeclaredSource recordInstall path and trigger
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/aryaniyaps/lamina --skill "brand/templates"
Safe inspection promptEditorial

Inspect the Agent Skill "lamina" from https://github.com/aryaniyaps/lamina/blob/af269ef3347fb7edeb956f3af9c943641717891c/brand/templates/SKILL.md at commit af269ef3347fb7edeb956f3af9c943641717891c. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Process

    Follow this sequence for design:

    Goal: [what they're trying to accomplish]Operations: [what they can trigger]Follow this sequence for design:
  2. 02

    Workflow: [Name]

    1. [Actor] → [Operation] → [Side effect]

    [Actor] → [Operation] → [Side effect]1. [Actor] → [Operation] → [Side effect]
  3. 03

    When to use

    Invoke Lamina when the task involves:

    New features where domain rules, user behavior, and system invariants all matterMulti-step flows (onboarding, checkout, settings, wizards)Permission-sensitive or multi-actor interactions
  4. 04

    1. Domain

    Define entities, states, and invariants:

    Define entities, states, and invariants:

Permission review

Static risk signals and limitations

No configured static risk pattern was detected

This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score91/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars111SourceRepository attention, not individual Skill quality
Compatibility3 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
aryaniyaps/lamina
Skill path
brand/templates/SKILL.md
Commit
af269ef3347fb7edeb956f3af9c943641717891c
License
Apache-2.0
Collected
2026-08-04
Default branch
main
View the original SKILL.md

Lamina — For Developers Who Build with AI

Design how it works.

Lamina runs alongside your AI coding agent — Cursor, Claude Code, Codex, Gemini, Pi. It helps you know what to build before you prompt: edge cases, UX gaps, product states, and invariants in a transactional product graph your agent implements. Verified with isolated Persona Missions after you ship. Does not write your app source.

When to use

Invoke Lamina when the task involves:

  • New features where domain rules, user behavior, and system invariants all matter
  • Multi-step flows (onboarding, checkout, settings, wizards)
  • Permission-sensitive or multi-actor interactions
  • Empty states, error handling, or edge cases tied to business rules
  • Post-build verification against a design contract
  • "Build me a dashboard/settings/app" requests that skip product thinking

Do not invoke Lamina for:

  • Visual design, color, typography, or layout polish (use your UI design skill)
  • Generating React/Vue/Svelte components directly
  • Pure backend/API design with no user-facing flow

Process

Follow this sequence for design:

1. Domain

Define entities, states, and invariants:

### Entity: [Name]
- States: [list]
- Invariants: [rules that must never break]
- Permissions: [who can do what]

2. Actors & workflows

Map who does what across the system:

### Actor: [Role]
- Goal: [what they're trying to accomplish]
- Operations: [what they can trigger]

## Workflow: [Name]
1. [Actor] → [Operation] → [Side effect]

3. UX flows

Map primary and alternate paths as numbered steps:

## Flow: [Name]

**Trigger:** [what starts this flow]
**Success:** [what "done" looks like]

1. [Step]
2. [Step]

### Alternate paths
- [Condition] → [different path]

4. Scenarios & edge cases

Enumerate violations and recovery:

### Scenarios
- [ ] [Specific scenario] → [Expected behavior]

Categories: empty states, errors, concurrency, boundaries, permissions, recovery.

Verify

After implementation, run verification:

  1. Resolve the active GraphVersion and source revision.
  2. Compile one independent Mission for every active Persona.
  3. Run each Mission through a capability-matched adapter.
  4. Publish normalized Evidence and HarnessResults through graphd.

Output format

Always output in this order:

  1. Domain (entities, invariants)
  2. Actors & workflows
  3. UX flows
  4. Scenarios & edge cases

End with a GraphVersion-pinned implementation projection for the coding agent:

## Handoff

GraphVersion: [resolved version id]
Source revision: [resolved source revision]
Framework: [user's stack, or "agnostic"]
Priority: [what to build first]
Defer: [what can wait]

Voice

  • Precise, structural, dev-native
  • No marketing language, no "revolutionary AI"
  • Specs are testable — if you can't write a test for it, rewrite it
  • Name things consistently (use IDs like flow.invite-member.step-3)

Integration

Lamina is unopinionated. Works alongside:

  • Any UI design skill (Impeccable, UI UX Pro Max, etc.)
  • Any UI library (shadcn, MUI, Chakra, Radix, Tailwind)
  • Any framework (React, Vue, Svelte, Next.js, Angular, Astro, mobile)
  • Any coding agent (Cursor, Claude Code, Codex, Gemini, Pi)

Never prescribe component names from a specific library unless the user specifies one. Never opinionated about context management or memory.

Brand

  • Tagline: Design how it works.
  • Position: Know what to build. Iterate faster.
  • Visual: Grey UX layer · Highlighter #FACC15 accent · dotted annotations · 3D meerkat mascot
  • Website: lamina.dev

Alternatives

Compare before choosing