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 recover-live-stategit 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/recover-live-state)<a href="https://agentmods.dev/skills/ttxttx1111/sts2-llm/recover-live-state"><img src="https://agentmods.dev/badge/skills/ttxttx1111/sts2-llm/recover-live-state/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/recover-live-state"><img src="https://agentmods.dev/badge/skills/ttxttx1111/sts2-llm/recover-live-state.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 | $0.00027 | $0.00267 |
| Opus 5 | $0.00014 | $0.00133 |
| Sonnet 5 | $0.00005 | $0.00053 |
| Haiku 4.5 | $0.00003 | $0.00027 |
Grade A, and why
recover-live-state 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.
What it actually says
恢复当前 live run
适用场景：先判断当前真实 live 状态，再决定下一步动作。
阅读顺序
AGENTS.mdREADME.mdSTARTUP.mddata\python-runtime\runtime-status.jsondata\python-runtime\runs\下最新 rundata\live\latest-standalone-player-step.jsondata\live\standalone-player-step-history.jsonldata\python-runtime\knowledge\lessons.jsondata\python-runtime\knowledge\playbook.json
输出
- 当前 live scene
- 当前 floor
- 最近的真实阻塞点
- 是游戏重开了还是只是 standalone loop 重启了
- 下一步最有价值的动作
约束
- 优先相信最新 live 证据，而不是旧 summary。
- 不要只看 step counter 就判断重开。
- 如果
continue_run健康可用，优先把它视为恢复路径。
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 · 35 lines · 27 tokens per session scan A 48fc06151ed2
recover-live-state is a skill published in the GitHub repository ttxttx1111/sts2-llm (41 stars, last pushed 1mo ago), licensed MIT. It adds 27 tokens to every session and 267 once invoked, about $0.0001 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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