Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aryaniyaps/lamina --skill templatesgit clone --depth 1 https://github.com/aryaniyaps/laminaWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aryaniyaps/lamina/templates)<a href="https://agentmods.dev/skills/aryaniyaps/lamina/templates"><img src="https://agentmods.dev/badge/skills/aryaniyaps/lamina/templates/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aryaniyaps/lamina/templates"><img src="https://agentmods.dev/badge/skills/aryaniyaps/lamina/templates.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00082 | $0.00983 |
| Opus 5.5 | $0.00033 | $0.00393 |
| Sonnet 5.5 | $0.00016 | $0.00197 |
| Haiku 4.5 | $0.00008 | $0.00098 |
Grade A, and why
lamina scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 148 lines · 82 tokens per session scan A 0150e108f15a
lamina is a skill published in the GitHub repository aryaniyaps/lamina (121 stars, last pushed 10d ago), licensed Apache-2.0. It adds 82 tokens to every session and 983 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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