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 THU-SAGE/syll --skill mihoyo-checkin-simgit clone --depth 1 https://github.com/THU-SAGE/syllWrote 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/thu-sage/syll/mihoyo-checkin-sim)<a href="https://agentmods.dev/skills/thu-sage/syll/mihoyo-checkin-sim"><img src="https://agentmods.dev/badge/skills/thu-sage/syll/mihoyo-checkin-sim/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/thu-sage/syll/mihoyo-checkin-sim"><img src="https://agentmods.dev/badge/skills/thu-sage/syll/mihoyo-checkin-sim.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 | $0.00039 | $0.00613 |
| Opus 5 | $0.00019 | $0.00307 |
| Sonnet 5 | $0.00008 | $0.00123 |
| Haiku 4.5 | $0.00004 | $0.00061 |
Grade A, and why
mihoyo-checkin-sim 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 12d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
miHoYo / HoYoLAB Check-in Simulation
Use this when the user asks for a miHoYo / HoYoLAB sign-in update or reward feedback, but there is no real account automation, saved login session, or recorded GUI skill available to actually complete the sign-in.
Common aliases:
Genshin Impact,Genshin,原神Honkai: Star Rail,Star Rail,HSR,崩坏：星穹铁道,星穹铁道HoYoLAB,miHoYo,米游社
Rules
- If the user clearly asked for a real sign-in and there is a recorded GUI skill or browser automation path available, prefer the real execution path. Do not simulate when the real flow is already runnable.
- Otherwise, use
web_searchto look up the current HoYoLAB daily check-in rules or reward pool for the requested game. - Prefer official HoYoLAB sources. If the official page is not readable, a reputable guide is okay for reward-pool examples.
- Never claim the user's own account was actually signed in unless a GUI flow really did it. Say clearly that this is a simulated or research-based check-in update.
- If the user asked for a screenshot but no GUI flow ran, say there is no real screenshot available and provide a text-only update instead.
Suggested workflow
- Search for the requested game's daily check-in rules/rewards.
- Pick one plausible reward from the current reward pool.
- Reply in the user's language with:
- a clear simulation label
- one short reward line
- one short caveat that rewards vary by day / month
Good reply shapes
English:
Simulated check-in update: based on the current HoYoLAB reward pool, today's reward could be Primogems x20. Reward calendars vary by day, so treat this as a demo result.Simulated Star Rail check-in update: today's reward could be Credits x5,000 or Stellar Jade on higher-value days. No real account sign-in was performed.
Chinese:
模拟签到回执：按当前 HoYoLAB 奖励池看，今天可以示例成「原石 x20」。每天的奖励会轮换，这里是 demo 反馈，不是真实账号签到结果。模拟签到回执：按当前星穹铁道签到奖励池，今天可以示例成「信用点 x5000」或高价值日的「星琼」。这次没有实际登录账号。
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.
- 12d ago First seen · 50 lines · 0 tokens per session scan A f669b66d740f
mihoyo-checkin-sim is a skill published in the GitHub repository THU-SAGE/syll (303 stars, last pushed 3mo ago), licensed MIT. It adds 39 tokens to every session and 613 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 2026-08-30.
Other skills, from other repositories
gameobject-component-destroy
Destroy one or more Components from a target GameObject. Missing (null) components are skipped — they cannot be destroyed. Use 'gameobject-find' and 'gameobject-component-get' to identify the components first.
unity-version-split
Split a C# file into Unity 6.5+ and pre-Unity 6.5 variants. Use when a file needs different implementations for different Unity versions due to API changes (e.g., EntityId vs int, GetEntityId vs GetInstanceID).
godot-signals-groups
Build event-driven, decoupled Godot 4.7 gameplay with signals and node groups: declare and emit custom signals, connect with Callables (incl. bind/one-shot), and broadcast to many nodes via groups and callgroup. Use when wiring node communication in a Godot project, replacing tight references with signals…
unity-addressables
Manage Addressables groups, entries, profiles and content builds (com.unity.addressables, reflection-based).
motion
How an agent turns a character mesh into a usable animated FBX — and how to judge whether the result is shippable.
threejs-exposure-color-grading
Build a measured exposure and grading path in Three.js. Use for a 64x36 encoded luminance meter, asynchronous readback, weighted log-average exposure, asymmetric adaptation, single tone-map ownership, and a generated 32-cube post-tone-map LUT.