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 ggg123124/vrchat-assistant --skill presence-statusgit clone --depth 1 https://github.com/ggg123124/vrchat-assistantWrote 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/ggg123124/vrchat-assistant/presence-status)<a href="https://agentmods.dev/skills/ggg123124/vrchat-assistant/presence-status"><img src="https://agentmods.dev/badge/skills/ggg123124/vrchat-assistant/presence-status/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/ggg123124/vrchat-assistant/presence-status"><img src="https://agentmods.dev/badge/skills/ggg123124/vrchat-assistant/presence-status.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 | $0.00000 | $0.01438 |
| Opus 5.5 | $0.00000 | $0.00575 |
| Sonnet 5.5 | $0.00000 | $0.00288 |
| Haiku 4.5 | $0.00000 | $0.00144 |
Grade A, and why
presence-status 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 23d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
presence-status —— 按「自己是否在游戏内」自动切换自定义状态文字
本文档给调用本插件的 AI Agent 看：这个插件能做什么、怎么用。
为什么需要它
本服务常驻登录 VRChat 账号（云服务器 24h 在线）时，自己在好友眼里长期是
"在网站上活跃"（位置 offline:offline）。使用者要求：
- 不在游戏内（挂机，服务还开着）→ 状态文字显示"挂机"提示（如
Bot挂机）； - 回到游戏内 → 恢复成上次下线时的那条状态文字（不是写死一套固定文案）。
核心的动态状态引擎（get_dynamic_status / set_dynamic_status）只支持 {online}
（在线好友数）一个变量，无法区分"自己是否在游戏里"；本插件补上这个能力。
能力
- get_presence_status：查询配置、核心自我在场判定（
in_game/not_in_game/unknown）、 已捕获的"上次下线时状态"savedText、最近一次写入与错误。 - set_presence_status：设置开关、挂机文案、轮询间隔、恢复用文字；可
syncNow立即同步一次。
配置项（存插件私有表 plg_presence-status_settings，跨重启保留）：
| 键 | 默认 | 说明 |
|---|---|---|
enabled |
false |
是否启用自动切换（默认关闭，需显式开启） |
idleTemplate |
挂机中（服务在线） |
不在游戏内时写入的状态文字（≤64 字符） |
pollSeconds |
60 |
轮询间隔秒（下限 20，上限 3600） |
savedText |
（自动捕获） | 回到游戏内时要恢复的文字。出游戏时自动捕获当前文案；也可手动指定（空串=清空，回到游戏后不改文字） |
工作方式：捕获 + 恢复（转换点触发）
在游戏内 ──检测到出游戏──▶ ① 读当前状态文字并捕获为 savedText（= 你上次下线的状态）
② 写入 idleTemplate（如 Bot挂机）
不在游戏 ──检测到进游戏──▶ 写回 savedText
- 只在转换点动作：进/出游戏各触发一次，之后不反复改写——你在别处手动改的状态文字会被保留 （不会被每次轮询抢回去）。
- 判定源：核心服务
dashboard.selfPresence的三态（见core/self-presence.js）。 - 不确定就不动：
unknown（无位置记录 / 位置陈旧超 1 小时 / 解析失败）时不翻转现状。 - 没有可恢复值时保护现状：
savedText为空（或恰好等于idleTemplate）时回到游戏内—— 若当前文案是你自己写的（非空、且不是本插件写入的挂机文案），保持不动并把它记为新的基线； 只有当现状已为空、或现状正是本插件写入的挂机文案时，才写入空串（避免把挂机文案留在"人在游戏里"的状态上）。 - 只改状态文字（
statusDescription），status种类原样回传，不改变在线形态。 - 与动态状态引擎互斥：核心
set_dynamic_status（按在线好友数改状态文字）与本插件写的是同一个statusDescription，代码里互不知情——两者同时启用时，挂机期间好友上下线会把挂机文案覆盖成"在线 N 人"， 回到游戏时本插件再写回捕获值，挂机提示因此不可靠。建议只启用其一（两个工具的 description 里也有同样提醒）。 - 防抖：两次 PUT 之间最小间隔 65 秒（与核心动态状态引擎同阈值）；目标文案已在位时不重复提交；
重启后从插件表恢复
lastState/savedText，不会因重启重复动作。 - 延迟：插件契约 v1.3 的 8 个 API 面没有事件订阅能力，因此按
pollSeconds轮询（默认 60s） ——进游戏方向最坏延迟约等于轮询间隔；出游戏方向还要先过核心的出游戏确认窗口 （core/self-presence.js的VRC_MONITOR_SELF_PRESENCE_OFFLINE_GRACE_SECONDS，默认 360s；窗口内一律判unknown、 本插件据此跳过写入），故最坏延迟 ≈ 轮询间隔 + 确认窗口（默认约 420s）。轮询只查本地 SQL（不产生 VRChat API 调用）， 每个转换点最多 2 次 API 调用（/auth/user+PUT /users/{id}）。
What ships with it
3 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.
- 23d ago Changed · +2 lines b44ee41c5a23
- 27d ago First seen · 80 lines · 0 tokens per session scan A 8287fb7d072c
presence-status is a skill published in the GitHub repository ggg123124/vrchat-assistant (26 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,438 tokens. 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 2026-09-19.
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