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 nimadorostkar/Claude-Skills-collection --skill mobile-releasegit clone --depth 1 https://github.com/nimadorostkar/Claude-Skills-collectionWrote 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/nimadorostkar/claude-skills-collection/mobile-release)<a href="https://agentmods.dev/skills/nimadorostkar/claude-skills-collection/mobile-release"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/mobile-release/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/nimadorostkar/claude-skills-collection/mobile-release"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/mobile-release.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 | $0.01046 |
| Opus 5 | $0.00018 | $0.00523 |
| Sonnet 5 | $0.00007 | $0.00209 |
| Haiku 4.5 | $0.00004 | $0.00105 |
Grade A, and why
mobile-release 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 8d 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.
Mobile Release
Purpose
Ship a mobile release safely. Unlike a web deploy, a bad mobile release cannot be rolled back — users have already installed it. The process must therefore prevent the bad release rather than recover from it.
When to Use
- Preparing a store submission.
- Setting up a mobile CI/CD pipeline.
- Responding to a crash spike after a release.
- Establishing a release process for a team that does not have one.
Capabilities
- Version and build-number strategy.
- Code signing and credential management.
- Staged rollout and kill switches.
- Crash and performance monitoring with alerting.
- Store review preparation and common rejection avoidance.
Inputs
- The build, its version, and what changed.
- Store credentials and signing keys.
- The current crash-free rate as a baseline.
Outputs
- A signed, reproducible build from CI.
- A staged rollout plan with defined abort criteria.
- Monitoring that will detect a regression before users report it.
Workflow
- Build in CI, never on a laptop — A build that only one machine can produce is a build you cannot reproduce when it breaks.
- Test the release build — On real devices, including the oldest supported OS version. Debug builds hide crashes that only occur under release optimization.
- Ship behind a flag — Anything risky is remotely toggleable. A feature flag is the only rollback a mobile app has.
- Stage the rollout — 1%, then 10%, then 50%, then 100%, with at least a day between steps. Watch the crash-free rate at each stage.
- Define the abort criteria before you start — For example: crash-free sessions below 99.5%, or any new crash affecting more than 0.1% of sessions. Halt the rollout automatically, do not debate it.
- Keep the previous build ready — On Android you can halt a staged rollout; on iOS you can only submit a new build. Have one prepared.
Best Practices
- A staged rollout is the only safety net that exists. Shipping to 100% immediately is a decision to have no rollback.
- Every release needs a kill switch for its risky feature. Server-side flags cost a day to build and save a release.
- Monitor the crash-free session rate, not the crash-free user rate. The latter hides a crash that occurs on one screen in ten sessions.
- Symbolicate crash reports in CI by uploading dSYMs and mapping files as part of the build. A crash report without symbols is useless at 2am.
- Never bump only the marketing version. The build number must increase on every submission or the store rejects it.
- Store review rejections cluster around permissions, in-app purchase rules, and misleading metadata. Read the guideline before you build the feature, not after the rejection.
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.
- 8d ago First seen · 101 lines · 36 tokens per session scan A 0776e78064f3
mobile-release is a skill published in the GitHub repository nimadorostkar/Claude-Skills-collection (26 stars, last pushed 24d ago), licensed MIT. It adds 36 tokens to every session and 1,046 once invoked, about $0.0002 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 2026-09-03.
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