prefab-partition-wall-solution

prefab-partition-wall-solution is a skill for Codex from eiway112/prefab-interior-skills. It costs 207 tokens per session (13,134 once invoked), scanned A, original, MIT.

A decision and verification guide for non-load-bearing interior walls, such as apartment dividing walls and room partitions. It compares light steel framing, ALC panels, and other wall systems for performance, cost, and construction needs.

In plain words
What is it for?
Use it to select or review partition-wall systems for homes, hotels, offices, hospitals, and rental housing. It supports performance checks, cost analysis, construction planning, and material-arrival inspection.
Why use it?
Choosing a wall system involves more than picking a product: sound insulation, fire resistance, constraints, cost assumptions, and installation details must all fit together. This guide provides a structured way to check a proposed solution against those requirements and applicable standards.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is **接口 Schema 详见**:../shared/interface-contracts.md IC-10 字段约束表 + JSON Schema(IC-10-Request / IC-10-Response);推理算法规则见 ../shared/standards-reasoning-rules.md.

Good fit Use it to select or review partition-wall systems for homes, hotels, offices, hospitals, and rental housing. It supports performance checks, cost analysis, construction planning, and material-arrival inspection.

Compare 6 skills from other repositories ↓
Install

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.

Clone the repo
git clone --depth 1 https://github.com/eiway112/prefab-interior-skills
agentmods
npx agentmods add skills/eiway112/prefab-interior-skills/prefab-partition-wall-solution

Made for: 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 prefab-partition-wall-solution

README.md
[![agentmods](https://agentmods.dev/badge/skills/eiway112/prefab-interior-skills/prefab-partition-wall-solution/github.svg)](https://agentmods.dev/skills/eiway112/prefab-interior-skills/prefab-partition-wall-solution)
Your own site
<a href="https://agentmods.dev/skills/eiway112/prefab-interior-skills/prefab-partition-wall-solution"><img src="https://agentmods.dev/badge/skills/eiway112/prefab-interior-skills/prefab-partition-wall-solution/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 prefab-partition-wall-solution

Your own site · 80×15
<a href="https://agentmods.dev/skills/eiway112/prefab-interior-skills/prefab-partition-wall-solution"><img src="https://agentmods.dev/badge/skills/eiway112/prefab-interior-skills/prefab-partition-wall-solution.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 207 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 13,134 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.
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 $0.00207 $0.13134
Opus 5 $0.00103 $0.06567
Sonnet 5 $0.00041 $0.02627
Haiku 4.5 $0.00021 $0.01313

Measured 6d ago against content hash 35c404409472, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

prefab-partition-wall-solution 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 6d 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.

技能仓备份/prefab-partition-wall-solution/SKILL.md · 437 lines

How it starts

The opening of the file, as written. The whole thing — 437 lines — stays where its author put it; the contents beside it link to each section on GitHub.

装配式隔墙方案技术顾问

角色定位

以装配式装修产业化为导向,整合规范标准、产品技术、工艺工法及工程案例,为民用建筑项目中的分户墙和室内隔墙等非承重隔墙,提供权威、精准、可落地的技术解决方案。

v2 认知模型升级:从"产品推荐器"转变为"决策方法论 + 验证引擎"。旧模型:"我有这些产品 → 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"。技能的知识分三层处理:原则红线层(不可逾越的硬约束)、方法论层(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(CG-20260817-001,2026-08-17):定义骨架增强试点——新增「工作流」块(需求确认→标准推理→验证执行→输出复核四阶段,含证据产物与阶段放行条件)与「成功指标(量化)」块(清单覆盖率/引用合规/数据来源标注/红线处理四条可证伪验收线 + 期望校准),按《技能定义骨架规范》v1.0 编写;方法论、红线体系、接口接线零变更。

历史:v2.0.3(CG-20260808-026,2026-08-08):IC-10/SRE 接线补全——验证执行清单新增"第 0 项:标准推理(IC-10)",跨技能协作原则新增 IC-10 调用规范(PW → SRE,含降级策略),新增红线 PW-R-P1-9"严禁跳过 SRE 标准推理"(PW 注册红线 18→19 条,对标 FL-R-P1-1/WS-R-P1-5/CL-R-P1-5)。

认知基础

技能对"什么是装配式隔墙"的定义、三大本质特征(工厂预制、干式工法装配、非承重)、三大品类分类框架(条板隔墙、龙骨隔墙、模块化/集成隔墙)及品类识别对验证逻辑的影响,详见 reference.md §一。该定义以 glossary.md(合集级共享术语库 §4.1)为统一基准。

核心价值主张:权威性(基于现行标准与验证实践)、系统性(方案选型-性能验证-成本控制-施工指导全链路覆盖)、实用性(可直接指导生产施工的具体参数与节点详图)。

方法论层(B层)

技能的核心能力输出层,详见 reference.md §四

  • B1 选型决策树(§4.A):4 步决策流程——锁定性能目标 → 明确约束条件 → 构造逻辑匹配 → 候选方案验证
  • B2 方案验证协议(§4.B):5 种输入分类(A-E)+ 三原则审查 + 专业计算验证 + 11 维度验证清单 + 结构化输出模板 + 文档三级分级
  • B3 成本分析框架(§4.C):造价构成模型 + 口径核查 + 敏感性分析与阶跃点
  • B4 施工控制通用原则(§4.D):通用工序验收 + 质量控制要点 + 封堵施工区分(引用 A4)
  • B5 功能适配性逻辑(§4.E):荷载约束 + 饰面-基层交互 + 挂载能力

验证执行检查清单

每次执行 B2 方案验证时,须逐项完成以下检查,确保不遗漏验证维度:

□ 0. 标准推理(Step 0):调用 IC-10(SRE 场景推理)确定适用标准集(含按项目所在地激活地方标准),作为后续各验证项的判据基准;SRE 不可用时按降级策略使用 PW 内置标准映射(PW-R-P1-9)
□ 1. 输入分类(B2.0):确认输入类型 A/B/C/D/E
□ 2. 隔声性能验证:查A1指标 + A2计算/检测报告(估算路径见 IC-03 调用规范)
□ 3. 耐火性能验证:查A1指标 + A3原理/检测报告
□ 4. 场景辨别:一般隔墙/防火隔墙/防火墙(A3.1)
□ 5. 封堵要求:隔声/防火/复合(A4体系)
□ 6. 厚度适配:总厚度 ≤ 空间约束
□ 7. 荷载适配:面密度 ≤ 楼板承载力(B5.1)
□ 8. 管线兼容:空腔深度满足敷设需求
□ 9. 饰面适配:基层满足预定饰面要求(B5.2)
□ 10. 挂载能力:基层握钉力及加固方案(B5.3)
□ 11. 构造合理性:声桥/密封/解耦(A2原理)
□ 12. 成本合理性:成本结构在合理区间(B3框架)
□ 13. 风险提示:标注不确定性和安全相关事项
□ 14. 输出模板:按B2.4结构化格式输出

工作流

方案验证类请求的固定执行阶段(Discovery→Planning→Execution→Review 映射为本技能四阶段)。纯知识咨询、术语问答类请求不走完整流程,但红线体系全程适用。本块按《技能定义骨架规范》v1.0(_专题_技能合集策划/技能定义骨架规范.md)编写,只固化流程不承载知识。

阶段 动作 证据产物 放行条件
1 需求确认 输入分类(B2.0 判定 A-E 型);确认项目类型、项目所在地、空间部位;关键参数缺失时先追问(联动 R-P1-6 低可靠性识别拒收) 输入类型判定 + 项目要素记录 输入类型确认且项目要素齐备(或用户明示按假设推进并记录假设)
2 标准推理 调用 IC-10(SRE)确定适用标准集(含按项目所在地激活地方标准);SRE 不可用时按降级策略使用 PW 内置标准映射并显式标注(PW-R-P1-9) 适用标准集(领域分组 + 判据指标来源) 标准集确定;标准集未确定不得进入验证执行
3 验证执行 逐项执行上方验证执行检查清单第 1-13 项;隔声估算需计算且无适用 CMA/CNAS 报告时经 IC-03 路由 ACE(双叶/多叶构造禁以单板简化式替代) 清单逐项结论(通过/不适用+理由/预估值+风险标注) 13 项均有结论或显式降级声明
4 输出复核 按 B2.4 输出模板结构化输出;逐项复核数据来源分级标注、"❓ 预估满足"标签、不确定性声明;红线回归扫描(P0-P2) 结构化方案验证输出(性能验证表/成本估算/施工控制点) 「成功指标(量化)」第 1-4 项全部满足

Read the full file on GitHub · 437 lines

Files

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.

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. 6d ago Changed 35c404409472
  2. 11d ago First seen · 437 lines · 207 tokens per session scan A 114b50c65292

Subscribe to this mod's changes

prefab-partition-wall-solution is a skill published in the GitHub repository eiway112/prefab-interior-skills (4 stars, last pushed 9d ago), licensed MIT. It adds 207 tokens to every session and 13,134 once invoked, about $0.0010 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

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…

microsoft/ai-agents-for-beginners · 200 tokens

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…

vercel/next.js · 95 tokens

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…

vercel/next.js · 83 tokens

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…

vercel/next.js · 170 tokens

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…

vercel/next.js · 103 tokens