390 skills · sorted by relevance
Plan technology strategy and engineering team growth with frameworks for technical debt, hiring, architecture decisions, and vendor evaluation. Use Python tools and decision templates to prioritize improvements, structure teams, and track engineering performance.
"Apply the Technology Acceptance Model (Davis, 1989) and Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003) to predict technology adoption. Use this skill when the user needs to evaluate user acceptance of a new system, diagnose adoption barriers, design interventions to improve technology uptake, or when they ask 'why aren't users adopting this', 'what drives technology acceptance', or 'how do we increase adoption rates'.".
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"Apply the TPACK framework to evaluate and design technology-integrated instruction at the intersection of technological, pedagogical, and content knowledge. Use this skill when the user needs to assess teacher readiness for technology integration, design professional development for ed-tech, or evaluate whether technology use is pedagogically grounded — even if they say 'how to integrate technology in teaching', 'ed-tech evaluation', or 'teacher technology competency'.".
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Knowledge base from the GAO Technology Readiness Assessment Guide (GAO-20-48G, 2020). Use for evaluating technology maturity in acquisition programs and projects: Technology Readiness Levels (TRL 1–9) and related scales (MRL, IRL), identifying Critical Technology Elements (CTEs), the five-step process for a high-quality TRA, the four characteristics of a reliable TRA (comprehensive, well-documented, credible, defensible), Technology Maturation Plans (TMPs), and using TRA results in knowledge-based, milestone decisions. Assessment/maturity oriented: it measures readiness and frames risk — it is not a full SE process model, cost-estimating, or schedule guide (see sibling packs for those).
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Plan technology investments and engineering team growth using structured assessments. Evaluate technical debt, compare building versus buying, document architecture choices, and define engineering health metrics to produce prioritized plans grounded in costs, risks, and business needs.
Guides privacy impact assessment for emerging technologies including IoT, blockchain, AR/VR, quantum computing, and digital twins. Covers risk identification methodology, proportionality assessment, and technology-specific privacy challenges. Activate when evaluating new technology adoption, innovation projects, or emerging tech procurement. Keywords: PIA, emerging technology, IoT, blockchain, AR/VR, quantum computing, digital twins, innovation privacy.
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半导体芯片制造工艺 (Semiconductor Process Engineering / 半导体芯片制造工艺 — 以「物理化学极限 + 良率经济双重约束」为特征的集成电路前道/后道制造工艺认知操作系统：从「器件架构与微缩路线（planar→FinFET→GAA nanosheet→CFET、等效微缩 DTCO/STCO、背面供电 BSPDN）→ 工艺整合（FEOL/MOL/BEOL 模块协同、PDK、流片 tape-out）→ 单元工艺（光刻 litho（DUV 浸没式 193i / EUV 13.5nm / 多重曝光 SADP-SAQP / OPC / mask）、刻蚀 etch（RIE/ICP/原子层刻蚀 ALE）、薄膜沉积 depo（CVD/PECVD/LPCVD/ALD/PVD/外延 epi/电镀 Cu）、掺杂 doping（离子注入 ion implant / 退火 RTA-laser anneal）、CMP 化学机械抛光、清洗 cleaning）→ 量测检测 metrology（CD-SEM / OCD / overlay / 椭偏 ellipsometry / 缺陷检测 defect inspection / e-beam）→ 良率工程 yield（缺陷密度 / SPC 统计过程控制 / FDC / APC / DOE 实验设计 / 良率爬坡 yield ramp）→ 先进封装 advanced packaging（2.5D/3D、CoWoS、HBM、混合键合 hybrid bonding、chiplet、TSV）」的完整器件-工艺-良率-量产决策链。覆盖 (a) 第一性张力 — **物理/化学/材料的硬约束（量子隧穿、短沟道效应、RC 延迟、热预算、缺陷物理、ppb 级污染控制）⇄ 良率/成本/产能的经济约束（每片晶圆成本、良率是主经济指标、D0 缺陷密度、wafer-per-hour、折旧）**；**持续微缩/摩尔定律（dimensional + equivalent scaling、节点路线图 N5/N3/N2/A16/A14、high-NA EUV）⇄ 物理极限/微缩放缓（原子尺度、漏电、功耗墙、成本墙、'摩尔定律已死'之争）**；**协同优化/整合（DTCO 设计-工艺协同、STCO 系统-工艺协同、模块间 trade-off）⇄ 单模块极致优化（单一 unit process 工艺窗口）**；**工艺配方的 tacit 手艺（process recipe 调试、工艺窗口、缺陷根因分析、量产 ramp 的经验）⇄ 可建模/可仿真/数据驱动（TCAD 仿真、ML 良率分析、APC/FDC、数字孪生）**；**性能-功耗-面积-成本 PPAC 四角权衡 ⇄ 良率/可制造性 DFM 优先**；**自主可控/国产替代（卡脖子、EUV 出口管制、设备/材料/EDA 国产化、SMIC/长江存储/长鑫/中微/北方华创/上海微电子）⇄ 全球高度分工（ASML 光刻垄断、AMAT/Lam/TEL/KLA 设备、TSMC/Samsung/Intel 代工、全球供应链）**。(b) 核心工作流 / pipeline（最标准、最易蒸高质量 + CLI 化）— 新节点/新工艺导入：器件目标与 PPAC 定义 → 工艺整合方案与 PDK → 单元工艺开发与配方调试（DOE 找工艺窗口）→ 量测建立与 SPC → 良率爬坡（缺陷分类 + 根因分析 + 工艺改善）→ 量产移交与持续改善。具体单元工艺 SOP：光刻（曝光条件 / OPC / overlay 控制 / 多重曝光分解）、刻蚀（选择比 / profile / loading effect / ALE）、沉积（台阶覆盖 / 应力 / 均匀性）、CMP（去除速率 / 碟形 dishing / 侵蚀 erosion）、量测与缺陷分析、良率分析与 FA 失效分析。(c) 工具栈 — 设备（光刻 ASML/上海微电子 SMEE；刻蚀+沉积 AMAT/Lam/TEL/中微 AMEC/北方华创 Naura；离子注入 AMAT/Axcelis；CMP AMAT/荏原 Ebara；量测检测 KLA/AMAT/中科飞测/上海精测）、EDA/TCAD/仿真（Synopsys Sentaurus/Silvaco/Coventor SEMulator3D、OPC Calibre/Synopsys）、良率与制造软件（SPC、MES、FDC/APC、缺陷分析 yield management、PWS）、材料（光刻胶 photoresist、CMP 浆料 slurry、特气、靶材、掩膜 mask blank）。(d) 知识正典 — 半导体工艺 canon 横跨器件物理与制造工程：核心教材（Plummer/Deal/Griffin《Silicon VLSI Technology》、Sze《Physics of Semiconductor Devices》《VLSI Technology》、Wolf & Tauber《Silicon Processing for the VLSI Era》、Campbell《Fabrication Engineering at the Micro and Nanoscale》、May & Spanos《Fundamentals of Semiconductor Manufacturing and Process Control》、Quirk & Serda《Semiconductor Manufacturing Technology》、肖国勇/施敏中文教材）、路线图（ITRS/IRDS、IEEE 国际器件与系统路线图）、顶会论文（IEDM、Symposium on VLSI Technology、IRPS 可靠性、SPIE Advanced Lithography、ISSCC、DAC）、行业分析（SemiAnalysis、TechInsights、IC Knowledge）。(e) figures/流派 — 学术与器件奠基（Gordon Moore 摩尔、Robert Dennard 登纳德微缩、胡正明 Chenming Hu FinFET/UTB-SOI 发明人 UC Berkeley、刘明 Tsu-Jae King Liu Berkeley、Krishna Saraswat Stanford、Mark Bohr Intel 工艺架构）、产业领袖与工艺大师（张忠谋 Morris Chang TSMC、林本坚 Burn-Jeng Lin 浸没式光刻、Martin van den Brink ASML、米玉杰/梁孟松 SMIC/三星工艺、Mark Liu/魏哲家 TSMC）、行业分析师（Dylan Patel SemiAnalysis、Scotten Jones IC Knowledge、TechInsights 拆解、Handel Jones）、科普与拆解（Asianometry、The Chip Letter、半导体行业观察）。流派分歧：等效微缩派 vs 摩尔定律已死派、前道微缩 vs 先进封装 chiplet 异构集成、dimensional scaling vs DTCO 协同优化、IDM vs 纯代工 foundry 模式、自主可控/国产替代路线 vs 全球分工。(f) 行业话术/黑话 — 制程节点 node / 流片 tape-out / 工艺窗口 process window / 良率 yield / 缺陷密度 D0 / 关键尺寸 CD / 套刻 overlay / 掩膜 reticle-mask / 光刻胶 PR / 浸没式 immersion / EUV/DUV / 多重曝光 multi-patterning SADP-SAQP / OPC / 刻蚀选择比 selectivity / profile / loading effect / 原子层刻蚀 ALE / 台阶覆盖 step coverage / 外延 epi / 离子注入 implant / 退火 anneal / RTA / CMP / dishing-erosion / FEOL-MOL-BEOL / FinFET / GAA / 纳米片 nanosheet / CFET / 背面供电 BSPDN / high-NA / PPAC / DTCO-STCO / DFM / SPC / FDC-APC / DOE / WAT-PCM / 良率爬坡 yield ramp / FA 失效分析 / particle 颗粒 / 洁净室 cleanroom-级别 / 12寸-8寸 wafer / chiplet / CoWoS / HBM / 混合键合 hybrid bonding / TSV / PDK / 等效微缩. (g) 争议/批判 — 「摩尔定律是否已死 vs 等效微缩继续」、「节点命名营销化（N3/N2 ≠ 物理 3nm/2nm，gate pitch/metal pitch 才是真尺度）」、「前道微缩 vs 先进封装异构集成谁是未来」、「自主可控/国产替代的现实（EUV 卡脖子、设备/材料/EDA 国产化进度、出口管制 entity list、良率与成熟度差距）」、「良率/成本/性能三角权衡」、「人才稀缺与工艺 know-how 的 tacit 性」、「中国大基金/产能扩张是否过剩」、「制裁与技术封锁」。(h) 大量隐性工艺手艺（process recipe 调试与工艺窗口寻找、缺陷根因分析与 FA、量产良率爬坡的经验判
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Use when a task needs the judgment of a Biofuels/Biodiesel Technology and Product Development Manager — deciding whether a lab/bench-scale process is ready to scale up, evaluating feedstock flexibility tradeoffs in process design, pricing a technology's value against regulatory credit pathways (RFS RIN, LCFS CI score), or managing IP strategy for a novel conversion process. Distinct from biofuels-production-manager, which runs an existing operating facility — this role owns R&D and commercialization of new or improved process technology.
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Create a copilot-instructions.md file from an existing codebase. Identify technology versions, architecture, naming conventions, and testing practices, then turn observed patterns into project-specific guidance for GitHub Copilot without introducing unsupported assumptions.
Compares frameworks, libraries, and cloud providers using weighted criteria. Helps teams choose technologies with estimates of five-year total ownership costs, security assessments, community health indicators, and migration effort, risks, and timelines.
Design or review a system’s overall structure, compare technology choices, and plan for growth and failures. Produce architecture diagrams and Architecture Decision Records, documents that explain key choices, alternatives, and their consequences.
Develop TPACK for integrating a specific technology or AI tool into subject teaching with pedagogical alignment. Use when adopting new ed-tech, reviewing AI tools, or planning technology integration.
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Secular technology trends, technology adoption cycle, disruption risk, AI impact analysis, digital transformation, industry 4.0 trends, technology moat, innovation trajectory, R&D effectiveness, tech competitive positioning
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Develop TPACK for integrating a specific technology or AI tool into subject teaching with pedagogical alignment. Use when adopting new ed-tech, reviewing AI tools, or planning technology integration.
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Plan insurance technology adoption. TRIGGERS - Use when user needs help with insurance-technology-plan related tasks.
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Evaluates insurtech business models with distribution innovation, underwriting technology, and claims automation. Use when analyzing insurtech, evaluating digital insurance, or assessing insurance technology.
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Evaluate and implement agricultural technology solutions. TRIGGERS - Use when user needs help with agricultural-technology related tasks.
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"Apply Affordance Theory (Gibson, 1979; Norman, 1988) to analyze the action possibilities that an artifact provides to an actor. Use this skill when the user needs to evaluate technology design from an affordance perspective, identify why users struggle with an interface, analyze IT-enabled organizational change through affordance actualization, or when they ask 'what does this technology afford', 'why can't users figure out this feature', or 'how does technology enable new practices'.".
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Expert-level nanotechnology covering nanomaterials, nanofabrication, characterization methods, nanoelectronics, nanomedicine, and self-assembly.
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Expert-level clinical engineering covering medical equipment management, hospital technology systems, healthcare IT integration, safety standards, and health technology assessment.
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Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
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Reviews a proposal, business case, deck or plan in character as a Chief Technology Officer archetype and returns a DRAFT review in the chat with a verdict, findings cited to the exact passage, technology risks (architecture, build versus buy, vendor lock-in, security of design, engineering capacity), what would change the verdict and five interrogation questions. Use when the user asks to "run a CTO review", "pressure-test the technical side of this plan", "what would a CTO ask about this" or "rehearse the technology seat before the review". Do not use for cash, payback or budget questions, use cfo-reviewer instead; for capacity and timeline questions, use coo-reviewer; for security controls, privacy or compliance, use ciso-reviewer. Drafts for human review; never approves, authorises or signs off.
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Evaluate and implement agricultural technology solutions. TRIGGERS - Use when user needs help with agricultural-technology related tasks.
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Audit a focused part of an existing codebase, reconstruct its behavior and past decisions, and record gaps in reasoning, coding practices, features, and technology choices. Use the findings to plan, test, implement, and verify improvements.