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.
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.
curl -O https://raw.githubusercontent.com/Jwuthri/Tracely-ai/master/.agents/skills/compose-graphics/SKILL.mdgit clone --depth 1 https://github.com/Jwuthri/Tracely-aiWrote 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/jwuthri/tracely-ai/compose-graphics)<a href="https://agentmods.dev/skills/jwuthri/tracely-ai/compose-graphics"><img src="https://agentmods.dev/badge/skills/jwuthri/tracely-ai/compose-graphics.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00036 | $0.04472 |
| Opus 5 | $0.00018 | $0.02236 |
| Sonnet 5 | $0.00007 | $0.00894 |
| Haiku 4.5 | $0.00004 | $0.00447 |
Grade A, and why
compose-graphics 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 7d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- compose-graphics — 100% identical, 0 lines differ
- compose-graphics — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 504 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compose Graphics
Advanced Compose visuals: M3 Expressive motion physics, AGSL shaders (Android 13+), Canvas / DrawScope, graphicsLayer effects. Loaded for advanced thesis (shader, expressive, M3 Expressive, AGSL, Canvas, holographic). Foundation:
../compose-motion/SKILL.mdcovers basics. Concise rules here. Deep-dive inreferences/.
Decision Tree: Which API for Which Need
| Need | API |
|---|---|
| Spring physics with bounce / overshoot | MotionScheme.expressive() (M3 Expressive) |
| Pixel-level shader | RuntimeShader + Modifier.graphicsLayer { renderEffect = ... } (Android 13+) |
| Generative drawing (paths, particles, fractals) | Canvas { drawScope -> ... } |
| GPU effects (blur, shadows, color filters) | Modifier.graphicsLayer { renderEffect = ... } or Modifier.blur(...) |
| Adaptive system materials (Material You glassmorphism) | Modifier.background(MaterialTheme.colorScheme.surfaceContainerHighest) |
| Liquid glass on Android | AGSL shader recipe (no native API like iOS yet) |
Domain 1: Material 3 Expressive
What It Is
The 2025 Material 3 evolution introduces spring-based motion physics replacing fixed-duration tweens. New shape morphing API via androidx.graphics.shapes. New MotionScheme selectable on the theme. Aimed at hero moments, key interactions, brand-defining UI.
MotionScheme
| Scheme | Personality | Use For |
|---|---|---|
MotionScheme.standard() |
Calmer, less overshoot | Default for chrome, lists, navigation |
MotionScheme.expressive() |
More overshoot, longer settle | Hero reveals, FABs, primary CTAs |
Apply on the theme:
MaterialTheme(motionScheme = MotionScheme.expressive()) {
// children read tokens via MaterialTheme.motionScheme.*
}
Tokens exposed:
| Token | Domain | Speed |
|---|---|---|
fastSpatialSpec() |
Position / size | < 200ms |
defaultSpatialSpec() |
Position / size | ~ 350ms |
slowSpatialSpec() |
Position / size | ~ 600ms |
fastEffectsSpec() |
Opacity / color | < 150ms |
defaultEffectsSpec() |
Opacity / color | ~ 250ms |
slowEffectsSpec() |
Opacity / color | ~ 400ms |
What ships with it
3 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.
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.
- 7d ago First seen · 504 lines · 36 tokens per session scan A 7b3889e783a2
compose-graphics is a skill published in the GitHub repository Jwuthri/Tracely-ai (1,193 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 4,472 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.
Other skills, from other repositories
eas-workflows
EAS service (paid). Helps understand and write EAS workflow YAML files for Expo projects. Use this skill when the user asks about CI/CD or workflows in an Expo or EAS context, mentions .eas/workflows/, or wants help with EAS build pipelines or deployment automation.
latex-submission-pipeline
Use when building a LaTeX manuscript submission pipeline with templates, latexmk, BibTeX/Biber, chktex, latexindent, CI PDF builds, compile debugging, and submission zip packaging.
github-actions
GitHub Actions workflow patterns for React Native iOS simulator and Android emulator cloud builds with downloadable artifacts. Use when setting up CI build pipelines or downloading GitHub Actions artifacts via gh CLI and GitHub API.
flutter-cicd
Set up CI/CD pipelines for Flutter apps. Use when configuring automated testing, build, or deployment workflows with GitHub Actions or Fastlane.
android-tooling
Configure Android static analysis with Detekt, Ktlint, and Android Lint for CI/CD quality gates. Use for Android-specific lint and quality tooling; defer generic Java Checkstyle, SonarQube, and standalone CI configuration.
app-store-deployment
Publishes mobile applications to iOS App Store and Google Play with code signing, versioning, and CI/CD automation. Use when preparing app releases, configuring signing certificates, or setting up automated deployment pipelines.