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 NSHipster/sosumi.ai --skill publicgit clone --depth 1 https://github.com/NSHipster/sosumi.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/nshipster/sosumi.ai/public)<a href="https://agentmods.dev/skills/nshipster/sosumi.ai/public"><img src="https://agentmods.dev/badge/skills/nshipster/sosumi.ai/public/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/nshipster/sosumi.ai/public"><img src="https://agentmods.dev/badge/skills/nshipster/sosumi.ai/public.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 | $0.00036 | $0.00952 |
| Opus 5.5 | $0.00014 | $0.00381 |
| Sonnet 5.5 | $0.00007 | $0.00190 |
| Haiku 4.5 | $0.00004 | $0.00095 |
Grade A, and why
sosumi 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 16d 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.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sosumi Skill
Use this skill to reliably fetch Apple docs as Markdown when coding agents need precise API details.
When to Use
Use Sosumi when the request involves any of the following:
- Apple platform APIs (
Swift,SwiftUI,UIKit,AppKit,Foundation, etc.) - API signatures, availability, parameter behavior, or return semantics
- Human Interface Guidelines questions
- WWDC session transcript lookup
- External Swift-DocC documentation (for example, GitHub Pages or Swift Package Index hosts)
Core Workflow
- If you already have a
developer.apple.comURL, replace the host withsosumi.aiand keep the same path. - If you do not know the exact page path, search first, then fetch the best match.
- Prefer specific symbol pages instead of broad top-level pages when answering implementation questions.
Optional CLI Preflight
If the Sosumi CLI is available, quickly verify local access before deeper debugging:
sosumi --versionconfirms the CLI is installed and onPATH.sosumi --helpshows top-level usage.sosumi <command> --helpis the manual for command-specific behavior.
HTTP Usage
Replace developer.apple.com with sosumi.ai:
- Original:
https://developer.apple.com/documentation/swift/array - AI-readable:
https://sosumi.ai/documentation/swift/array
Content Types
Apple API Reference
- Pattern:
https://sosumi.ai/documentation/{framework}/{symbol} - Examples:
https://sosumi.ai/documentation/swift/arrayhttps://sosumi.ai/documentation/swiftui/view
Human Interface Guidelines
- Pattern:
https://sosumi.ai/design/human-interface-guidelines/{topic} - Examples:
https://sosumi.ai/design/human-interface-guidelineshttps://sosumi.ai/design/human-interface-guidelines/foundations/color
Apple Video Transcripts
- Pattern:
https://sosumi.ai/videos/play/{collection}/{id} - Examples:
https://sosumi.ai/videos/play/wwdc2021/10133https://sosumi.ai/videos/play/meet-with-apple/208
What ships with it
10 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.
- 16d ago Changed · +1 lines 858b3080a57e
- 2mo ago First seen · 100 lines · 36 tokens per session scan A 4530e014b049
sosumi is a skill published in the GitHub repository NSHipster/sosumi.ai (483 stars, last pushed 16d ago), licensed MIT. It adds 36 tokens to every session and 952 once invoked, about $0.0001 per session on Opus 5.5. 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.
sosumi compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| sosumiNSHipster/sosumi.ai | Skill | 483 | 16d ago | MIT | A | 36 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |