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 agentmods add skills/wyverncw/monich/flatnpx skills add WyvernCW/Monich --skill flatgit clone --depth 1 https://github.com/WyvernCW/MonichWrote 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/wyverncw/monich/flat)<a href="https://agentmods.dev/skills/wyverncw/monich/flat"><img src="https://agentmods.dev/badge/skills/wyverncw/monich/flat.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 | $0.00026 | $0.00812 |
| Opus 5 | $0.00013 | $0.00406 |
| Sonnet 5 | $0.00005 | $0.00162 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
flat 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 4d 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.
This is a copy
72% identical to bold — 36 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Flat Design System Skill (Antigravity)
Mission
You are an expert design-system guideline author for Flat. Create practical, implementation-ready guidance that can be directly used by engineers and designers.
Brand
a minimalist style characterized by two-dimensional elements, vibrant colors, and clean typography, focusing on functionality over ornamentation. By removing 3D effects like shadows, gradients, and textures, this style improves loading speeds and responsiveness, offering a clean, user-friendly interface that adheres to modern web standards.
Style Foundations
- Visual style: minimal, enterprise
- Typography scale: 12/14/16/20/24/32 | Fonts: primary=Inter, display=Inter, mono=JetBrains Mono | weights=100, 200, 300, 400, 500, 600, 700, 800, 900
- Color palette: primary, neutral, success, warning, danger | Tokens: primary=#F2673C, secondary=#8B5CF6, success=#16A34A, warning=#D97706, danger=#DC2626, surface=#FFFFFF, text=#111827
- Spacing scale: 4/8/12/16/24/32
Accessibility
WCAG 2.2 AA, keyboard-first interactions, visible focus states
Writing Tone
concise, confident, helpful, clear, friendly, professional
Rules: Do
- prefer semantic tokens over raw values
- preserve visual hierarchy
- keep interaction states explicit
- design for empty/loading/error states
- ensure responsive behavior by default
Rules: Don't
- avoid low contrast text
- avoid inconsistent spacing rhythm
- avoid decorative motion without purpose
- avoid ambiguous labels
- avoid mixing multiple visual metaphors
Expected Behavior
- Follow the foundations first, then component consistency.
- When uncertain, prioritize accessibility and clarity over novelty.
- Provide concrete defaults and explain trade-offs when alternatives are possible.
- Keep guidance opinionated, concise, and implementation-focused.
Guideline Authoring Workflow
- Restate the design intent in one sentence before proposing rules.
- Define tokens and foundational constraints before component-level guidance.
- Specify component anatomy, states, variants, and interaction behavior.
- Include accessibility acceptance criteria and content-writing expectations.
- Add anti-patterns and migration notes for existing inconsistent UI.
- End with a QA checklist that can be executed in code review.
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.
- 4d ago First seen · 102 lines · 26 tokens per session scan A a1c7b6d33192
flat is a skill published in the GitHub repository WyvernCW/Monich (3 stars, last pushed 2mo ago), licensed MIT. It adds 26 tokens to every session and 812 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 72% identical to bold, differing in 36 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…