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 rshankras/claude-code-apple-skills --skill variable-rewardsgit clone --depth 1 https://github.com/rshankras/claude-code-apple-skillsWrote 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/rshankras/claude-code-apple-skills/variable-rewards)<a href="https://agentmods.dev/skills/rshankras/claude-code-apple-skills/variable-rewards"><img src="https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/variable-rewards.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 5.1 | $0.00045 | $0.03350 |
| Opus 5 | $0.00023 | $0.01675 |
| Sonnet 5 | $0.00009 | $0.00670 |
| Haiku 4.5 | $0.00005 | $0.00335 |
Grade A, and why
variable-rewards 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 3d 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 — 386 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Variable Rewards Generator
Generate a variable reward system — randomized rewards (daily spins, mystery boxes, bonus points) that leverage variable-ratio reinforcement to increase engagement. Implements ethical engagement patterns with daily/weekly caps, transparent probability disclosure, and no pay-to-play mechanics.
When This Skill Activates
Use this skill when the user:
- Asks to "add daily rewards" or "daily spin" mechanic
- Wants a "reward system" or "random rewards"
- Mentions "mystery box" or "loot box" (non-paid)
- Asks about "bonus system" or "daily bonus"
- Wants "gamification rewards" or "engagement rewards"
- Mentions "reward wheel" or "spin to win"
- Asks about "variable rewards" or "intermittent reinforcement"
Pre-Generation Checks
1. Project Context Detection
- Check Swift version (requires Swift 5.9+)
- Check deployment target (iOS 17+ / macOS 14+ for @Observable and SwiftData)
- Check for SwiftData availability and existing model container setup
- Identify source file locations
2. Conflict Detection
Search for existing reward or points systems:
Glob: **/*Reward*.swift, **/*Points*.swift, **/*DailySpin*.swift, **/*MysteryBox*.swift
Grep: "reward" or "dailySpin" or "mysteryBox" or "rewardPool" or "lootBox"
If existing reward system found:
- Ask if user wants to replace or extend it
- If extending, generate only the missing components
3. Platform Detection
Determine if generating for iOS or macOS or both (cross-platform). The templates use SwiftUI and are cross-platform by default.
Configuration Questions
Ask user via AskUserQuestion:
-
Reward types? (multi-select)
- Points (numeric currency the user accumulates)
- Items (unlockable content: themes, stickers, avatars)
- Features (time-limited feature unlocks)
- Badges (collectible achievement badges)
- Mixed (all of the above) -- recommended
-
Reward mechanism?
- Daily spin (wheel animation, one spin per day)
- Mystery box (card-flip or chest-open, one per day)
- Random bonus (surprise toast notification on qualifying action)
- Multiple (daily spin + random bonus) -- recommended
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.
- 3d ago First seen · 386 lines · 45 tokens per session scan A 2507ff064a24
variable-rewards is a skill published in the GitHub repository rshankras/claude-code-apple-skills (701 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 3,350 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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flame-harness-evaluator
Phase 6 — skeptical QA. Run the game, watch it, then judge against the contract. Default = functional check; --strict adds quality and edge-case passes.
flame-harness-design
Phase 3 — define the Flutter designtokens.dart spec (palette, typography, spacing), the game's art/visual concept, and the asset/audio sourcing plan.
flame-harness-retro
Phase 11 — score the completed pipeline against Anthropic's 9 harness principles plus game quality, and write the retrospective.
flame-harness-build
Phase 8 — bootstrap signing credentials, generate fastlane config from templates, and build + upload signed IPA (TestFlight) and AAB (internal track).