Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/eiway112/prefab-interior-skillsnpx agentmods add skills/eiway112/prefab-interior-skills/prefab-ceiling-systemWrote 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/eiway112/prefab-interior-skills/prefab-ceiling-system)<a href="https://agentmods.dev/skills/eiway112/prefab-interior-skills/prefab-ceiling-system"><img src="https://agentmods.dev/badge/skills/eiway112/prefab-interior-skills/prefab-ceiling-system/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/eiway112/prefab-interior-skills/prefab-ceiling-system"><img src="https://agentmods.dev/badge/skills/eiway112/prefab-interior-skills/prefab-ceiling-system.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 | $0.00146 | $0.10312 |
| Opus 5 | $0.00073 | $0.05156 |
| Sonnet 5 | $0.00029 | $0.02062 |
| Haiku 4.5 | $0.00015 | $0.01031 |
Grade A, and why
prefab-ceiling-system 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.
How it starts
The opening of the file, as written. The whole thing — 469 lines — stays where its author put it; the contents beside it link to each section on GitHub.
装配式吊顶系统 — 决策与验证引擎
§1 角色定位
| 项目 | 定义 |
|---|---|
| 技能标识 | CL |
| 技能名称 | prefab-ceiling-system |
| 定位 | 装配式吊顶与顶面部品系统的决策方法论与验证引擎 |
| 核心原则 | 所有输出结论基于物理原理和标准规范,不基于产品营销话术;声学输出一律为贡献量口径 |
v2 认知模型升级:从 v1 的"吊顶方案推荐"升级为"决策方法论 + 验证引擎"。旧模型:"我有这些吊顶方案 → 你的需求匹配哪个 → 推荐给你";新模型:"你有任何方案 → 我帮你系统验证 → 你做出决策"。技能知识分三层处理:原则红线层(A 层,不可逾越的硬约束)、方法论层(B 层,核心能力输出)、演示示例层(方法论运作载体)。
版本说明:v2.1.0 为实质 v2 重构定稿(原标 2.0.0 实为 v1 范式,名实不符,见 change-governance CG-20260807-021)。v2.1.1(CG-023,2026-08-08):阶段 7 条文 S1 批量核验整改,关键性能指标与关键约束汇总表状态字段同步跃迁(7 项待核验全部获条文级定位,5 处 v1 错误修正)。v2.1.2(CG-024,2026-08-08):阶段 8 QA 修复轮——examples.md 示例 3 D8 平整度档位更正(金属板档→矿棉板档)与版本头对齐、reference.md §2.1 基线计数同步(63→67 条);红线基线首轮回读 WARN 三项整改(§7 新增原则 7"拒绝绝对化断言"、P1-1/P2-2 应对话术补充声明,registry §十一同步)。v2.1.3(CG-025,2026-08-08):SRE 运行时发布涟漪修正——§12 文件清单 SRE 指针改为 shared 镜像实际路径(表述澄清级,方法论零变更)。
核心能力矩阵:
| 能力 | 说明 | 支撑体系 |
|---|---|---|
| 选型决策 | 四技术路线×多场景的决策树 | B1 选型决策树 |
| 隔声贡献估算 | 通过 IC-09 调用 ACE,贡献量口径(±4-6 dB) | B2 验证协议 Step 3 + B5 |
| 验证协议 | 六步骤全流程验证(SRE→解析→审查→计算→核验→组装) | B2 验证协议 |
| 机电协同与检修 | 空腔利用、标高核算、检修口布置 | B3 机电协同与检修口 |
| 施工指导 | 关键控制点与验收标准 | B4 施工控制 |
与 FL/PW 的声学协作边界:
| 维度 | CL 管辖 | FL/PW 管辖 |
|---|---|---|
| 声学角色 | 吊顶对宿主构件(楼板/分户墙)隔声的贡献量估算 | 宿主构件达标判据:FL 管楼板(L'nT,w/Ln,w),PW 管隔墙(Rw+C/DnT,w+C) |
| 达标归属 | 不独立判达标(CL-R-P2-3) | 达标归属宿主构件标准(GB 55038-2025 / GB 50118-2010 未废止条文) |
| 红线 | CL-R-P2-3(贡献量标注) | FL-R-P0-1 / PW 对应红线 |
§2 认知基础
技能对"什么是装配式吊顶系统"的定义(三要素:支承体系、空腔功能层、面板体系)、三维分类矩阵与四技术路线,详见 reference.md §一。该定义以 ../shared/glossary.md(合集级共享术语库)为统一基准。
核心价值声明:CL 的所有输出结论基于物理原理和标准规范,不基于产品营销话术;吊顶隔声输出为贡献量估算,不作为构件隔声判据。
认知基线指针:
| 内容 | 指针 |
|---|---|
| 定义与分类框架 | → reference.md §一 |
| 标准层次与引用规则 | → reference.md §二 |
| 原理红线层(A 层) | → reference.md §三 |
§3 方法论层摘要
B1-B5 核心能力概述
| 编号 | 能力 | 核心内容 | 指针 |
|---|---|---|---|
| B1 | 选型决策树 | 场景识别→技术路线→龙骨/面板选型→约束校验 | → reference.md §四 B1 |
| B2 | 验证协议 | 六步骤全流程(SRE→解析→审查→计算→核验→组装) | → reference.md §四 B2 |
| B3 | 机电协同与检修口 | 标高核算、检修策略、机电点位协调 | → reference.md §四 B3 |
| B4 | 施工控制 | 流程原则、关键控制点、质量通病防治 | → reference.md §四 B4 |
| B5 | 隔声贡献估算 | IC-09 调用规范(必传集/解读规则/降级链/记录模板) | → reference.md §四 B5 |
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.
- 10d ago First seen · 469 lines · 146 tokens per session scan A b2cfb19e2085
prefab-ceiling-system is a skill published in the GitHub repository eiway112/prefab-interior-skills (4 stars, last pushed 9d ago), licensed MIT. It adds 146 tokens to every session and 10,312 once invoked, about $0.0007 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…