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 WellApp-ai/Well --skill state-machinegit clone --depth 1 https://github.com/WellApp-ai/WellWrote 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/wellapp-ai/well/state-machine)<a href="https://agentmods.dev/skills/wellapp-ai/well/state-machine"><img src="https://agentmods.dev/badge/skills/wellapp-ai/well/state-machine/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/wellapp-ai/well/state-machine"><img src="https://agentmods.dev/badge/skills/wellapp-ai/well/state-machine.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 | $0.00014 | $0.00919 |
| Opus 5.5 | $0.00006 | $0.00368 |
| Sonnet 5.5 | $0.00003 | $0.00184 |
| Haiku 4.5 | $0.00001 | $0.00092 |
Grade A, and why
state-machine 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
State Machine Skill
Document the state machine for UI components, comparing current behavior to expected behavior and mapping all state transitions.
When to Use
- During Ask mode CONVERGE loop for stateful components
- When refactoring existing components with complex state
- Before implementing new interactive UI components
Instructions
Phase 1: Identify States
List all possible states for the component:
| State | Current Behavior | Expected Behavior |
|---|---|---|
| Initial | [What happens now] | [What should happen] |
| Loading | [Current loading UX] | [Expected loading UX] |
| Success | [Current success display] | [Expected success display] |
| Error | [Current error handling] | [Expected error handling] |
| Empty | [Current empty state] | [Expected empty state] |
Common States to Consider:
| State Type | Examples |
|---|---|
| Data states | Initial, Loading, Success, Error, Empty, Stale |
| Interaction states | Idle, Hover, Focus, Active, Disabled |
| Visibility states | Hidden, Visible, Collapsed, Expanded |
| Selection states | Unselected, Selected, Partially selected |
| Validation states | Valid, Invalid, Pending validation |
Phase 2: Map Transitions
Define what triggers each state change:
| From | To | Trigger | Side Effects |
|---|---|---|---|
| Initial | Loading | User action / Mount | Start fetch |
| Loading | Success | Data received | Populate UI |
| Loading | Error | Request failed | Show error message |
| Loading | Empty | Empty response | Show empty state |
| Error | Loading | Retry clicked | Restart fetch |
| Success | Loading | Refresh clicked | Refetch data |
Phase 3: State Diagram
Create a Mermaid state diagram:
stateDiagram-v2
[*] --> Initial
Initial --> Loading : fetch
Loading --> Success : data received
Loading --> Error : request failed
Loading --> Empty : no data
Error --> Loading : retry
Success --> Loading : refresh
Empty --> Loading : refresh
Success --> [*] : unmount
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 · 133 lines · 14 tokens per session scan A c88b772ce795
state-machine is a skill published in the GitHub repository WellApp-ai/Well (345 stars, last pushed 6d ago), licensed MIT. It adds 14 tokens to every session and 919 once invoked, about $0.0001 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.
Other skills, from other repositories
scalar-design-system
Scalar's design system — design tokens, theming (@scalar/themes), CSS variables, and the @scalar/components library. Use when designing or implementing Scalar UI, especially with Paper (code-to-design / design-to-code), so output matches real Scalar tokens, colors, typography, spacing, and components instead of…
luxury
Minimalist high-fashion design with editorial serif headlines, ivory and near-black palette, antique gold accents, sharp edges and generous whitespace.
pagible
Dark, immersive design with blue-purple gradient accents, sharp edges, and a deep navy background for a modern tech aesthetic.
premium
Warm, professional design with burgundy red brand accents, large rounded cards, alternating sections, and bold typography.
style
Luxe fashion-commerce editorial design with a deep-indigo canvas, oversized numerals, large image-led storytelling, rounded capsules/cards, and restrained monochrome accents.
clean
Simplicity-focused design with ample whitespace, legible typography, and a limited color palette to reduce visual clutter.