Tracely-ai: Skill for Claude Code

.agents/skills/desktop-principles/SKILL.md

desktop-principles is a skill for Claude Code, Codex from Jwuthri/Tracely-ai. It costs 36 tokens per session (2,960 once invoked), scanned A, original, MIT.

A set of user-interface guidelines for desktop software and desktop-sized websites on macOS, Windows, Linux, and the web. It covers pointer use, keyboard shortcuts, multiple windows, and focus—the indication of which control receives keyboard input.

In plain words
What is it for?
Use it when designing or reviewing desktop interfaces, including hover states, keyboard navigation, shortcuts, multiple windows, and focus management.
Why use it?
It helps avoid interfaces that feel unclear or difficult to use with a mouse and keyboard. In particular, it explains how hover feedback, focus handling, and desktop interaction patterns should work.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument; installed under .agents/ (shared by several agents).

This is Jwuthri/Tracely-ai's own configuration. It tells Claude Code and Codex how to work on Tracely-ai itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Tracely-ai configures →

About the project

Tracely is a CI/CD system for AI agents that turns failed production traces into replayable regression tests. Development teams use it to detect and group agent failures, run the resulting cases on pull requests, and block changes that reproduce those failures. The catalogue entries provide skills for operating this trace-based testing and observability workflow.

Jwuthri/Tracely-ai · 1,216 stars · on GitHub · tracely-ai.com

Reuse

Borrowing it

Nothing to install: this file belongs to Jwuthri/Tracely-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Jwuthri/Tracely-ai/master/.agents/skills/desktop-principles/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Jwuthri/Tracely-ai

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for desktop-principles

README.md
[![agentmods](https://agentmods.dev/badge/skills/jwuthri/tracely-ai/desktop-principles.svg)](https://agentmods.dev/skills/jwuthri/tracely-ai/desktop-principles)
Your own site
<a href="https://agentmods.dev/skills/jwuthri/tracely-ai/desktop-principles"><img src="https://agentmods.dev/badge/skills/jwuthri/tracely-ai/desktop-principles.svg" alt="Measured on agentmods" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,960 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00036 $0.02960
Opus 5 $0.00018 $0.01480
Sonnet 5 $0.00007 $0.00592
Haiku 4.5 $0.00004 $0.00296

Measured 8d ago against content hash 1c52aeca8760, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

desktop-principles 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 8d 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

.agents/skills/desktop-principles/SKILL.md · 364 lines

How it starts

The opening of the file, as written. The whole thing — 364 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Desktop Principles

Desktop UX context. Loaded when desktop is detected (macOS, Windows, Linux desktop, web desktop). Concise rules here. Deep-dive in references/.


Hover States Are Mandatory

Hover is the primary affordance signal on desktop, the inverse of mobile. A pointer hovering over a target without immediate visual feedback feels broken: users rely on :hover to confirm an element is interactive before committing to a click. Every clickable surface must have a distinct hover style, ideally with a 100-200ms transition so the change is perceptible without feeling sluggish.

CSS - hover styles for interactive elements:

.button {
  background: var(--surface);
  transition: background 120ms ease-out, transform 120ms ease-out;
}

.button:hover {
  background: var(--surface-hover);
  transform: translateY(-1px);
}

.button:active {
  transform: translateY(0);
}

SwiftUI - .onHover for macOS, .hoverEffect for iPadOS:

struct ToolbarButton: View {
  @State private var hovering = false

  var body: some View {
    Image(systemName: "square.and.arrow.up")
      .padding(8)
      .background(hovering ? Color.gray.opacity(0.15) : .clear)
      .onHover { hovering = $0 }
      .animation(.easeOut(duration: 0.12), value: hovering)
      .hoverEffect(.highlight) // iPadOS pointer support, no-op on macOS
  }
}

Compose Desktop - onPointerEvent or hoverable + interactionSource:

@OptIn(ExperimentalComposeUiApi::class)
@Composable
fun ToolbarButton(onClick: () -> Unit) {
  val interactionSource = remember { MutableInteractionSource() }
  val hovered by interactionSource.collectIsHoveredAsState()

  Box(
    modifier = Modifier
      .hoverable(interactionSource)
      .background(if (hovered) Color.LightGray.copy(alpha = 0.15f) else Color.Transparent)
      .clickable(onClick = onClick)
      .padding(8.dp),
  ) { Icon(Icons.Default.Share, contentDescription = "Share") }
}

Pointer Precision

Mouse and trackpad pointers are far more accurate than thumbs, so desktop targets can be smaller than the 44pt mobile minimum. Common ranges are 24-32px for icon buttons, 28-36px for toolbar items. WCAG 2.5.8 (AA, target size minimum) sets the absolute floor at 24x24 CSS pixels for non-mobile pointer input. Sub-24px targets need spacing or be grouped with sibling targets.

Read the full file on GitHub · 364 lines

Files

What ships with it

2 files 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.

Changes

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.

  1. 8d ago First seen · 364 lines · 36 tokens per session scan A 1c52aeca8760

Subscribe to this mod's changes

desktop-principles is a skill published in the GitHub repository Jwuthri/Tracely-ai (1,216 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 2,960 once invoked, about $0.0002 per session on Opus 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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