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 gyh20062008-commits/re-ios --skill ios-reverse-engineeringgit clone --depth 1 https://github.com/gyh20062008-commits/re-iosWrote 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/gyh20062008-commits/re-ios/ios-reverse-engineering)<a href="https://agentmods.dev/skills/gyh20062008-commits/re-ios/ios-reverse-engineering"><img src="https://agentmods.dev/badge/skills/gyh20062008-commits/re-ios/ios-reverse-engineering/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/gyh20062008-commits/re-ios/ios-reverse-engineering"><img src="https://agentmods.dev/badge/skills/gyh20062008-commits/re-ios/ios-reverse-engineering.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00091 | $0.00769 |
| Opus 5 | $0.00046 | $0.00385 |
| Sonnet 5 | $0.00018 | $0.00154 |
| Haiku 4.5 | $0.00009 | $0.00077 |
Grade A, and why
ios-reverse-engineering 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 9d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
iOS Reverse Engineering
Use this skill for authorized static analysis of iOS artifacts. Keep the workflow offline and evidence-focused: identify what is present in the artifact, record limitations, and do not interact with real backends.
Safety Rules
- Only analyze artifacts the user is authorized to inspect.
- Do not bypass FairPlay DRM, app-store encryption, account protections, certificate pinning, or legal restrictions.
- Do not extract, exfiltrate, validate, or use account credentials, tokens, cookies, or session material.
- Do not attack, fuzz, replay, or probe real production services discovered in strings.
- If a binary is encrypted or analysis is limited, report the limitation and request an authorized debug, enterprise, decrypted, or source-derived build.
Quick Workflow
Run the bundled scripts from scripts/ in this order. The output directory defaults to ios_analysis_out.
scripts/check_deps.sh
scripts/ios_unpack.sh <target> [output_dir]
scripts/ios_fingerprint.sh <target> [output_dir]
scripts/ios_macho_analyze.sh <target> [output_dir]
scripts/ios_class_scan.sh [output_dir]
scripts/ios_api_scan.py [output_dir]
scripts/ios_report.py [output_dir]
The final report is written to:
<output_dir>/analysis-report.md
The endpoint and API clue inventory is written to:
<output_dir>/endpoints.json
What To Inspect
- App identity:
Info.plist, bundle ID, executable name, version, URL schemes, associated domains. - Entitlements: app groups, keychain groups, associated domains, push, iCloud, network extension, app sandbox signals.
- Bundle layout: embedded frameworks, dylibs, app extensions, watch apps, resources, dSYM DWARF files.
- Mach-O: architecture slices, encryption load commands, linked libraries, rpaths, symbols, Objective-C metadata, Swift symbols, strings.
- API clues: hardcoded URLs, domains, REST-like paths, GraphQL operations, WebSocket schemes, and client framework names.
References
Load these only when useful:
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.
- references/api-extraction-patterns.md 1.3 KB
- references/ios-analysis-checklist.md 1.9 KB
- references/macho-notes.md 1.5 KB
- scripts/check_deps.sh 901 B runs code
- scripts/ios_api_scan.py 5.3 KB runs code
- scripts/ios_class_scan.sh 2.3 KB runs code
- scripts/ios_fingerprint.sh 5.8 KB runs code
- scripts/ios_macho_analyze.sh 3.2 KB runs code
- scripts/ios_report.py 5.4 KB runs code
- scripts/ios_unpack.sh 2.9 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.
- 9d ago First seen · 73 lines · 91 tokens per session scan A be85f5263387
ios-reverse-engineering is a skill published in the GitHub repository gyh20062008-commits/re-ios (1 stars, last pushed 2mo ago), licensed MIT. It adds 91 tokens to every session and 769 once invoked, about $0.0005 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 2026-08-31.
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