debug-through-player-chat

debug-through-player-chat is a skill for Claude Code, Codex from ttxttx1111/sts2-llm. It costs 34 tokens per session (365 once invoked), scanned A, original, MIT.

A troubleshooting guide for live game runs that uses player chat to find out what the player currently sees and believes. It helps separate a reasoning mistake from a wrong game state or an execution problem.

In plain words
What is it for?
Use it when a live game is stuck, a player may have misunderstood the scene, or the available actions are unclear. It suggests questions about the current scene, key action, rejected alternatives, missing information, and execution response.
Why use it?
It prevents organizers from assuming that the runtime or code is broken before checking the player’s understanding. This avoids unnecessary code changes and system-level guesses.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when a live game is stuck, a player may have misunderstood the scene, or the available actions are unclear. It suggests questions about the current scene, key action, rejected alternatives, missing information, and execution response.

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Install with agentmods
npx agentmods add skills/ttxttx1111/sts2-llm/debug-through-player-chat
Install

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.

Any agent
npx skills add ttxttx1111/sts2-llm --skill debug-through-player-chat
Clone the repo
git clone --depth 1 https://github.com/ttxttx1111/sts2-llm

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for debug-through-player-chat

README.md
[![agentmods](https://agentmods.dev/badge/skills/ttxttx1111/sts2-llm/debug-through-player-chat/github.svg)](https://agentmods.dev/skills/ttxttx1111/sts2-llm/debug-through-player-chat)
Your own site
<a href="https://agentmods.dev/skills/ttxttx1111/sts2-llm/debug-through-player-chat"><img src="https://agentmods.dev/badge/skills/ttxttx1111/sts2-llm/debug-through-player-chat/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.

agentmods 80×15 button for debug-through-player-chat

Your own site · 80×15
<a href="https://agentmods.dev/skills/ttxttx1111/sts2-llm/debug-through-player-chat"><img src="https://agentmods.dev/badge/skills/ttxttx1111/sts2-llm/debug-through-player-chat.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 365 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00034 $0.00365
Opus 5.5 $0.00014 $0.00146
Sonnet 5.5 $0.00007 $0.00073
Haiku 4.5 $0.00003 $0.00036

Measured 1mo ago against content hash 1c66812e13c2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

debug-through-player-chat 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 1mo 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.

deprecated/3/ai-play-slts2-2/.github/skills/debug-through-player-chat/SKILL.md · 47 lines

What it actually says

通过 player-chat 调试

适用场景:

  • 用户怀疑 player 判断不对
  • live run 卡住了,但还不知道是 scene 误判、API 异常还是 player 理解错误
  • 需要组织者先和 player 对话求证,而不是马上改代码

默认做法

先用:

python -m ai_play_slts2.cli player-chat --player-backend copilot_acp

应该追问什么

优先追问这些问题:

  1. 你现在看到的 scene 是什么?
  2. 你认为当前最关键的可选动作是什么?
  3. 你为什么排除其它动作?
  4. 你是否缺少额外检查信息,例如 deck / draw pile / discard pile / menu 状态?
  5. 你卡住是因为判断不清,还是因为执行层没有按预期响应?

目的

这条技能的目的不是“让组织者替 player 决策”,而是:

  • 让 player 把当前理解显式说出来
  • 快速区分问题来源:
    • player 推理问题
    • scene / 状态识别问题
    • live API / 执行问题

约束

  • 不要一上来就默认是 runtime 或代码 bug。
  • 不要跳过求证过程,直接给一堆系统层假设。
  • 如果问题可以通过对话澄清,就先不要引入新的包装层。
Changes

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.

  1. 1mo ago First seen · 47 lines · 34 tokens per session scan A 1c66812e13c2

Subscribe to this mod's changes

debug-through-player-chat is a skill published in the GitHub repository ttxttx1111/sts2-llm (41 stars, last pushed 3mo ago), licensed MIT. It adds 34 tokens to every session and 365 once invoked, about $0.0001 per session on Opus 5.5. 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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