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 ttxttx1111/sts2-llm --skill choose-live-entrypointgit clone --depth 1 https://github.com/ttxttx1111/sts2-llmWrote 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/ttxttx1111/sts2-llm/choose-live-entrypoint)<a href="https://agentmods.dev/skills/ttxttx1111/sts2-llm/choose-live-entrypoint"><img src="https://agentmods.dev/badge/skills/ttxttx1111/sts2-llm/choose-live-entrypoint/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/ttxttx1111/sts2-llm/choose-live-entrypoint"><img src="https://agentmods.dev/badge/skills/ttxttx1111/sts2-llm/choose-live-entrypoint.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 | $0.00031 | $0.00640 |
| Opus 5 | $0.00015 | $0.00320 |
| Sonnet 5 | $0.00006 | $0.00128 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
choose-live-entrypoint 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 10d 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.
What it actually says
选择当前入口
适用场景：
- 用户问“现在该怎么启动”
- 用户问“CLI 有什么用”
- 用户问“该用哪个命令”
- 需要在 直接打牌、对话调试、环境检查 三类动作里做选择
先判断目标
先判断用户当前真正想做什么：
- 直接继续当前 run / 让 player 打牌
- 先和 player 聊天，确认它看到了什么、怎么想
- 先检查环境、API、菜单、当前状态
推荐映射
1. 直接继续当前 run
用：
python -m ai_play_slts2.cli standalone-player-live --steps 20
说明：
- 这是当前活动体系里的主执行路径
- 含义是 player 直接连 live API 打牌
- 适合“先让系统继续往前走”
2. 先和 player 对话调试
用：
python -m ai_play_slts2.cli player-chat --player-backend copilot_acp
说明：
- 这是组织者和 player 的对话入口
- 适合“先问清楚它为什么这么判断”
- 不替 player 落子，而是帮助暴露问题
3. 先检查环境 / API / 当前状态
常用命令：
python -m ai_play_slts2.cli doctor
python -m ai_play_slts2.cli read-state
python -m ai_play_slts2.cli read-menu
python -m ai_play_slts2.cli bootstrap-live
说明：
doctor：检查 live API 是否可用read-state：读取当前游戏状态read-menu：读取当前菜单状态bootstrap-live：做 live 环境准备
应该怎么解释 CLI
当用户问“CLI 是什么”时，默认这样解释：
CLI 是这个仓库的命令行入口。
skill 负责教 agent 怎么想，CLI 负责把这些能力以终端命令的形式启动出来。
可以进一步拆成三类：
- 执行入口：
standalone-player-live - 对话调试入口：
player-chat - 运维检查入口：
doctor/read-state/read-menu/bootstrap-live
约束
- 不要再把
loop-live-runtime、supervise-live说成当前推荐入口。 - 不要把 CLI 说成“额外的一层智能”。
- 遇到入口选择问题，优先按“用户当前目标”来分流，而不是按旧 runtime 习惯回答。
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.
- 10d ago First seen · 89 lines · 31 tokens per session scan A 178df6c2e980
choose-live-entrypoint is a skill published in the GitHub repository ttxttx1111/sts2-llm (41 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 640 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.
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