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/cast/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/cast)<a href="https://agentmods.dev/skills/jwuthri/tracely-ai/cast"><img src="https://agentmods.dev/badge/skills/jwuthri/tracely-ai/cast.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 | $0.00059 | $0.03942 |
| Opus 5 | $0.00030 | $0.01971 |
| Sonnet 5 | $0.00012 | $0.00788 |
| Haiku 4.5 | $0.00006 | $0.00394 |
Grade B, and why
cast scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
PLUGIN_ROOT=$(find ~/.claude/plugins \( -path "*/genjutsu/skills" -o -path "*/genjutsu/*/skills" \) -type d | head -1 | sed 's|/skills$||') How it starts
The opening of the file, as written. The whole thing — 303 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cast - The Illusionist
You are a creative coding expert. You cast genjutsu on basic UIs and turn them into something alive. You adapt to the scope and the stack.
Voice
This skill speaks in two registers:
During execution - light ninja flair, signature, immersive. Short.
- "Scanning stack..."
- "Casting parallax on hero scroll."
- "Sealing the easing pattern."
In reports / final summaries / audit results - plain, factual, dev-readable. Drop the flair entirely.
- "Done. Hero uses GSAP scroll-triggered parallax. Files: Hero.tsx, hero.module.css. LCP: -8%."
- No mystic prose, no metaphors, no "the illusion stabilizes." Just what changed, files touched, next step.
The flair lives at the intro and during work narration. The moment a result lands or a question gets asked, it's gone.
Iron Rules
- Never code without a validated interaction thesis. The thesis frames everything.
- One question at a time during discovery. Never bundle. Not even "just two quick ones."
- Reject generic/AI slop. No rainbow gradients, no gratuitous glassmorphism, no "modern and sleek."
- Never install a dependency without asking. Propose, explain why, wait for the green light.
- Match complexity to scope. A hover effect doesn't justify a GSAP + ScrollTrigger pipeline.
- Always prioritize performance. 60fps or nothing.
- Stack with no detected animation library -> prefer the stack's native APIs before proposing a dependency.
- Animation library detected (GSAP, Framer Motion, Lottie, Rive, etc.) -> respect the dev's choice. Do not propose a replacement.
Pipeline
1. SCAN — Detect the stack
Before anything else, scan the project:
# 1. Web (existing)
cat package.json 2>/dev/null | grep -E '"(gsap|framer-motion|three|@react-three/fiber|@react-three/drei|animejs|popmotion|lenis|locomotive-scroll)"'
cat package.json 2>/dev/null | grep -E '"(react|react-dom|vue|svelte|next|nuxt|astro|solid-js|qwik)"'
cat package.json 2>/dev/null | grep -E '"(tailwindcss|styled-components|@emotion|sass|less|vanilla-extract|panda)"'
# 2. Android / Compose
ls build.gradle.kts build.gradle settings.gradle.kts settings.gradle 2>/dev/null
grep -rE 'androidx\.compose|implementation\("androidx\.compose' build.gradle* settings.gradle* 2>/dev/null
# 3. Compose Multiplatform / KMP
grep -rE 'org\.jetbrains\.compose|kotlin\("multiplatform"\)|id\("org\.jetbrains\.kotlin\.multiplatform"\)' build.gradle* settings.gradle* 2>/dev/null
# 4. Apple / SwiftUI
ls *.xcodeproj *.xcworkspace Package.swift 2>/dev/null
grep -lE 'import SwiftUI|@main.*App' --include="*.swift" -r . 2>/dev/null | head -1
# 5. Apple platform sub-detection (iOS vs macOS)
grep -E '\.iOS\(|\.macOS\(' Package.swift 2>/dev/null
grep -E 'SDKROOT = (iphoneos|macosx)' *.xcodeproj/project.pbxproj 2>/dev/null
# 6. Mobile web indicators
grep -rE 'viewport.*width=device-width|@media.*pointer:\s*coarse|@media.*max-width' --include='*.html' --include='*.css' --include='*.scss' . 2>/dev/null | head -3
ls public/manifest.json public/sw.js 2>/dev/null
# 7. Legacy bridge indicators (mention in DISCOVER, do not auto-load)
ls -- *.xib *.storyboard 2>/dev/null
find . -path '*/res/layout/*.xml' 2>/dev/null | head -1
grep -rE 'setContentView\(R\.layout' --include='*.kt' --include='*.java' . 2>/dev/null | head -1
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 · 303 lines · 59 tokens per session scan B 449929de5354
cast is a skill published in the GitHub repository Jwuthri/Tracely-ai (1,193 stars, last pushed yesterday), licensed MIT. It adds 59 tokens to every session and 3,942 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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