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 zhuanggenhua/BoardGame --skill ui-audit-loopgit clone --depth 1 https://github.com/zhuanggenhua/BoardGameWrote 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/zhuanggenhua/boardgame/ui-audit-loop)<a href="https://agentmods.dev/skills/zhuanggenhua/boardgame/ui-audit-loop"><img src="https://agentmods.dev/badge/skills/zhuanggenhua/boardgame/ui-audit-loop/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/zhuanggenhua/boardgame/ui-audit-loop"><img src="https://agentmods.dev/badge/skills/zhuanggenhua/boardgame/ui-audit-loop.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 | $0.00114 | $0.08579 |
| Opus 5.5 | $0.00046 | $0.03432 |
| Sonnet 5.5 | $0.00023 | $0.01716 |
| Haiku 4.5 | $0.00011 | $0.00858 |
Grade A, and why
ui-audit-loop 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
UI Audit Loop
把 UI 验收当成独立门禁。代码正确、元素存在、点击成功和 E2E 通过都不能单独证明玩家看到的界面合格。
用户可见图验收触发口径
截图 / 录屏审计和打开图片 / 录屏是稳定交付候选的最终验收动作，不是每次过程性 UI 修改的默认门禁；换句话说，开图或开录屏是完整重构或稳定候选完成后的胜利号角，不是实现过程中的例行动作。只有当本轮 UI 已经完成到可以宣称“可验收 / 可交付”、用户明确要求截图验收/玩家视角检查/打开图/录屏，或测试虽通过但界面仍存在高风险可用性疑点时，才进入本循环。
仍在搭建框架、跑通功能链、修流程、处理临时测试界面、占位 UI，或后续步骤会继续改造同一界面时，只做与当前风险匹配的功能、结构或私有诊断；局部截图不得进入用户可见查看器、对话内联或 PASS 目录。不得因为改了可见 UI 就主动把中间图或诊断录屏当作最终验收物打开给用户。用户可见交付必须是整屏整体，口径以 e2e-verification 和 show-image-to-user 为准。等完整重构完成并形成稳定候选后，再按本 skill 产出真实入口截图 / 录屏、AI 图面裁决和用户可见最终图 / 录屏。
新交互 / 新 UI 的端到端覆盖要求由 .spec/knowledge/standards/e2e-verification.md 与 .spec/knowledge/standards/ui-change-gates.md 维护；它要求覆盖矩阵和真实页面 E2E，但不等于每轮都打开图片、录屏或重跑全量截图。进入本 skill 时，只处理稳定候选或用户明确要求的图面 / 动效审计；用户可见展示仍必须等同一组图或录屏明确 PASS 后才允许。
- 先 AI 验，再给用户验：助手必须先检查原始最终候选截图 / 录屏做玩家视角审计，明确写出图面 / 动效事实、
PASS/REVISE结论、失败点或通过理由。用户已明确要求“打开图 / 录屏”但当前尚未PASS时，不得展示；继续审计或返工。不得先产生 PureRef / 系统查看器 / Codex 内联图 /view_image/Viewed Image等用户可见事件，再把它冒充验收。 - 验收范围只限本轮要求（强制）：进入截图验收时，先把用户本轮明确要求拆成可判定清单，例如“推斥必须看到来源唤醒 / 飞行路径 / 命中帧”“传送必须看到来源轨迹落点”“截图说明必须中文”。
PASS只要求这些清单项全部达标。不要把整页 UI、其它系统、非目标布局缺陷或历史未完成项塞进本轮硬门禁；它们只能作为备注，除非它们直接让本轮清单项无法被截图证明。反过来，E2E 绿、像素亮点、文件存在或其它非目标证据，也不能替代清单项本身达标。 - 本轮新增或改造的可见 UI 自动进入视觉范围（强制）：用户本轮清单若包含新增、改造或返工的可见界面，这些界面的视觉质量属于本轮要求，不能只验元素存在、可点击或 E2E 绿。最低必须按
ui-change-gates判定正式素材优先、同一信息一个主承载、每个可见元素唯一职责、提示 UI 不冒充承接物、关闭不占内容槽位。空态“暂无”、自我命名 CTA 和同屏重复横幅不得记成非本轮基础问题。本条只补触发条件，不复制那些质量规则正文。 - 未解决本轮问题禁止开图（强制）：如果用户刚指出的问题本身还没有直接证据证明已解决，不能因为“其它 UI 通过”“E2E 通过”“截图已经生成”“只是想让用户看一下”而开图。开图门禁只问本轮要求有没有逐条达标；非本轮问题不升级为阻塞，非本轮通过项也不计入达标。
- 用户可见展示只在触发后执行：当用户明确要求看图 / 打开图 / 截图验收 / 录屏，或本轮交付物本身就是图片型验收图 / 动效验收录屏时，同一张原始验收图、同一组原始验收图或同一份录屏被选为最终候选且 AI 判定
PASS后，必须交给项目show-image-to-user入口展示，再汇报完成。若本轮只是补 evidence、盘点截图 / 录屏、汇报测试或记录核图结论，未触发用户可见展示时，只汇报路径和结论，不自动打开查看器。 - 不通过就循环：只要 AI 判定
REVISE，且失败项属于当前 UI 目标范围，就继续改同一实现、回同一真实入口重拍、重新审计；不得把失败图交给用户人工挑错，也不得等用户催促才继续。 - 流程 UI 默认多图：如果 UI 改动涉及进入、选择、投掷、翻页、展开/关闭、前后状态、PC/移动对照或完整链路，最终验收物默认是有序截图集，而不是只给最新一帧。每张图必须用中文说明它证明哪一步；用户本轮点名的每个状态都要有对应原始整屏图，缺一项就判
REVISE。 - 动效验收通过后优先录屏展示：如果本轮验收对象是召唤、攻击、投射物、伤害飘字、拖拽、翻页或其它连续动画，关键帧截图仍用于 AI 自检和证据定位；当用户明确要看实际效果且本轮清单已
PASS后，最终用户展示优先使用短录屏 / GIF，而不是让用户从多张静态截图推断动作连贯性。录屏只证明它覆盖的那段动作，不能替代未录到阶段的验收。 - 联系表不能替代逐图审计：contact sheet、拼图、缩略图或低清总览只能用于索引和初筛；涉及目标选择、对象可读、遮挡、候选高亮、按钮归属或多步流程时，本轮变化媒体必须用不向用户展示的方式检查对应原始截图。未改写且已有有效 PASS 的媒体沿用记录，不要求再打开原图。没有对本轮变化媒体检查原图，就不得输出
PASS或把该图放入最终验收集；如果当前宿主没有私有看图能力，只能停在证据不足或补非展示型机器检查，不能先把未通过图打开给用户。 - 逐图账本是最终门禁：最终媒体目录中的每一张图 / 每一段录屏都必须登记目标对象、动作前后、玩家可见结果、同屏保护槽位、遮挡 / 裁切 / 内部 ID 泄漏检查和
PASS | REVISE | carried-forward。任一条为REVISE，整组只能保留为失败 / 诊断证据，禁止生成最终PASSmanifest、finalPassBeforeOpen: true或VIEWER_URL。账本全量不等于每轮重读全部原图。 - 逐图账本必须可机器校验：最终清单必须写入
visualReview.mode=all-media、claimScope=interaction-ui、reviewer.kind=subagent和逐媒体报告文件；报告条目数、路径和状态必须与media/images一一对应。视觉报告只判 UI / 交互可见性，不承担数值或规则正确性，后者必须回到 Vitest / 领域测试。增量核图、必须重读范围、carried-forward和固定悬浮层不得逼走主栏，以e2e-verification为唯一主源。 - 用户指出后只失效相关结论：用户话语分类以
conversation-handoff-target-lock为准。仅当用户点名某张图不合格或新增验收条件时，才把被点名 / 被新条件覆盖的图面结论降为历史 / 诊断并重拍重审；陈述、观察和流程问题不触发整组失效。E2E 绿灯、DOM 存在、截图生成成功和 viewer 注册不得恢复已失效条目的旧PASS。 - 阻塞口径：如果真实入口、截图生成、素材加载或图面审计被环境阻断，只能按阻塞汇报，说明现实后果、证据、为什么阻止继续、最小补救动作；不得宣称 UI 已完成。
What ships with it
5 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.
- 12d ago Changed · +3 lines a643d3aa900d
- 19d ago Changed 8e6885402949
- 22d ago Changed · +2 lines 5f9fdde6517e
- 28d ago Changed · -5 lines bb0c58df25c0
- 1mo ago Changed · +1 lines 3e0294fac75f
- 1mo ago First seen · 172 lines · 114 tokens per session scan A e0f8a0cf75ce
ui-audit-loop is a skill published in the GitHub repository zhuanggenhua/BoardGame (24 stars, last pushed yesterday), licensed MIT. It adds 114 tokens to every session and 8,579 once invoked, about $0.0005 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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