Orkas is a desktop application for commanding a team of AI agents through one chat, with a commander model assigning work to specialist agents in parallel or in sequence. People use it to coordinate research, writing, presentations, and software tasks while keeping files on their computer. The catalogue includes skills for extending the agents available to Orkas.
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 Orkas-AI/Orkas --skill b1f384166705git clone --depth 1 https://github.com/Orkas-AI/OrkasWrote 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/orkas-ai/orkas/b1f384166705)<a href="https://agentmods.dev/skills/orkas-ai/orkas/b1f384166705"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/b1f384166705/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/orkas-ai/orkas/b1f384166705"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/b1f384166705.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 | $0.00003 | $0.01187 |
| Opus 5 | $0.00002 | $0.00593 |
| Sonnet 5 | $0.00001 | $0.00237 |
| Haiku 4.5 | $0.00000 | $0.00119 |
Grade A, and why
swiftui-dev 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 11d 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
1 near-identical copy found in the catalogue:
- swiftui-dev — 86% identical, 19 lines differ
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.
SwiftUI Dev
Use this skill for SwiftUI development, architecture, structure, performance, and Apple native app profiling. It combines:
- SwiftUI view refactor and Observation/MV guidance.
- SwiftUI code-first performance audit.
- Native macOS/iOS Time Profiler CLI workflow with
xctrace,atos, and included scripts.
Do not use this skill for web performance, server profiling, generic PR review, product planning, or non-Apple UI frameworks. For ordinary implementation work without SwiftUI architecture/performance/native profiling concerns, use the development skill.
Route The Work
| User intent | Read |
|---|---|
Refactor SwiftUI View structure, split large body, review Observation boundaries |
SwiftUI refactor |
| Decide whether MV, framework-native state, or a ViewModel is justified | MV patterns |
| SwiftUI page is slow, scrolling janks, or body updates too often | SwiftUI performance |
| Build a dependency/update mental model before deeper profiling | WWDC23 performance model |
| Inspect current SwiftUI Instrument lanes or Cause & Effect evidence | SwiftUI Instruments workflow and SwiftUI timeline guide |
| Diagnose a main-thread hang or run-loop stall | App hangs guide |
| Record/analyze macOS or iOS native Time Profiler traces from CLI, symbolicate and rank hotspots through the standard Orkas Skill Runner | Native trace workflow |
If the user provides only symptoms, start with code-first SwiftUI review. Ask for trace/screenshots only when code review is inconclusive or the user explicitly wants trace analysis.
Required Inputs
For SwiftUI code review:
- Target view or feature code.
- Data flow:
@State,@Binding,@Environment,@Observable,@Query, services, models. - Symptoms and reproduction steps.
- Device/OS/build configuration when performance is involved.
What ships with it
12 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.
- _meta.json 844 B
- references/demystify-swiftui-performance-wwdc23.md 1.8 KB
- references/mv-patterns.md 7.7 KB
- references/native-trace.md 4.2 KB
- references/optimizing-swiftui-performance-instruments.md 1.8 KB
- references/swiftui-performance.md 2.9 KB
- references/swiftui-refactor.md 2.6 KB
- references/understanding-hangs-in-your-app.md 1.2 KB
- references/understanding-improving-swiftui-performance.md 2.2 KB
- scripts/extract_time_samples.py 1.1 KB runs code
- scripts/record_time_profiler.py 1.2 KB runs code
- scripts/top_hotspots.py 4.0 KB runs code
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.
- 11d ago First seen · 102 lines · 3 tokens per session scan A 54bb91ce2aaa
swiftui-dev is a skill published in the GitHub repository Orkas-AI/Orkas (1,885 stars, last pushed today), licensed MIT. It adds 3 tokens to every session and 1,187 once invoked, about $0.0000 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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