'construction' 검색 결과

Reviews Web Audio API JavaScript/TypeScript code for correctness, thread safety, and deprecated patterns. Use when the user asks to review AudioWorklet code, check an AudioWorkletProcessor, audit Web Audio graph construction, or diagnose crackling/dropouts in a web audio app. Trigger on phrases like "review my Web Audio code", "check my AudioWorklet", "is my AudioWorkletProcessor safe", or "why does my web audio crackle".

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Audit an existing Lamport-style hierarchical mathematical proof forward for validity and whether its hierarchy, scope, dependencies, side conditions, and proof constructs discharge the stated theorem. Use when the central question concerns a top-down proof with numbered levels, subproofs, ASSUME/PROVE, SUFFICES, PICK, CASE, DEFINE, Q.E.D., or prose equivalents. For an ordinary proof that first needs source-preserving hierarchy, use convert-lamport; for conclusion-first AND/OR obligation reconstruction, use reverse-lamport. Do not use to generate or replace a proof, or to audit Lean, Coq, Isabelle, or other proof-assistant source.

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基于已有项目做重构/新建（搬家不重写）的完整流程 Skill。当用户需要从现有混乱项目迁移到干净新项目时激活，引导完成：新项目文件夹 → PM功能清单 → 技术架构+红蓝推演（回写闭环）→ Cursor规范配置 → 分Phase构建。区别于 role-技术架构师（后者设计新技术方案）：本 Skill 是迁移型，先盘点已有资产，再设计去哪里放。触发词：「基于已有项目重构」「重构方案」「新建项目并迁移」「搬家不重写」「从零开始但复用现有代码」「项目架构整改」。

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Complete methodology for computing publication-quality cumulative abnormal returns with proper event-study test statistics, matching the robustness of Kaspereit's eventstudy2 for Stata. Covers dateline construction, event-date mapping, estimation and event windows, thin-trading adjustment, OLS with Theil prediction error correction, abnormal return computation, CAR/CAAR/AAR accumulation, boundary contamination guards, and common tests such as Patell, BMP, Kolari-Pynnonen, generalized sign, Wilcoxon, and GRANK-T. Use when the user mentions abnormal returns, event windows, market-model regressions, CARs, CAAR, AAR, eventstudy2, thin trading, trade-to-trade returns, or event-study test statistics.

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Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend="cupy64" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT.

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Unity physics query correctness patterns. Catches common mistakes with Raycast, SphereCast, OverlapSphere, NonAlloc allocation, LayerMask construction, trigger interaction, hit ordering, and query type selection. PATTERN format: WHEN/WRONG/RIGHT/GOTCHA. Based on Unity 6.3 LTS.

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Use when behavior-preserving frontend refactoring focuses on function API shape, flags, dependencies, mutability, construction, or command/function trade-offs, and the selected technique needs family-specific mechanics, risks, and JavaScript/TypeScript/React/Vue adaptation.

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Author, validate, test, and deploy YARA-L 2.0 detection rules and evaluate end-to-end detection coverage gaps in Google SecOps. Use when writing new detection rules, tuning existing rules, validating syntax, testing logic against historical telemetry, or evaluating detection coverage against threat intelligence blogs, CVE disclosures, and Threat Detection Opportunities (TDOs) using synthetic UDM events and long-running coverage analysis. Don't use for alert triage (use secops-triage), deep forensic event reconstruction on infected hosts (use secops-investigate), or case management operations (use secops-cases).

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Conduct rigorous cross-study meta-analysis of scRNA-seq data from ENCODE, integrating multiple single-cell transcriptomic datasets for a tissue/cell type. Use when the user wants to answer "what cell types exist in my tissue and what genes define them?" by combining scRNA-seq data across donors, labs, and platforms. Follows the Mawla et al. 2019 framework for assessing cross-study reproducibility, TIN-based quality filtering, and detection-limit-aware interpretation. Handles batch correction (Harmony/Seurat), dropout awareness, cross-contamination artifacts, and platform-specific biases. Use this skill for ANY scRNA-seq integration task, cross-dataset comparison, cell atlas construction, or reproducibility assessment involving ENCODE single-cell data.

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Integrate multiple ENCODE data types (RNA-seq, ATAC-seq, Histone ChIP-seq, TF ChIP-seq) for a tissue/cell type to build a comprehensive regulatory landscape. Use when the user wants to answer "what are the enhancers, promoters, and regulatory elements active in my tissue, and which transcription factors control them?" by layering expression, chromatin accessibility, histone marks, and TF binding data. Follows the Mawla et al. 2023 framework for cross-assay integration of islet cell type-specific data. Handles chromatin state annotation (ChromHMM), enhancer-gene linkage, TF motif enrichment, and cell type-specific regulatory element identification. Use for ANY multi-omic analysis, enhancer discovery, regulatory network construction, or epigenomic characterization using ENCODE data.

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Use this skill when designing, auditing, or troubleshooting behavioral boundaries for Agentforce agents — including topic (now subagent) Scope fields, agent-level system instructions, topic/action filters, the Escalation topic, restricted topics, and Instruction Adherence monitoring. Trigger keywords: agent guardrails, agent out of scope, restrict agent behavior, topic scope, subagent scope, agent fallback, Escalation topic, abuse prevention, action filters. NOT for Trust Layer content filtering (Einstein Trust Layer is a separate product concern), NOT for general topic routing design (use agentforce/agent-topic-design), NOT for prompt template construction (use agentforce/prompt-builder-templates).

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Use when creating a new Experience Cloud site: selecting LWR vs Aura template, configuring branding and navigation, setting up a custom domain, and using Experience Builder. Trigger keywords: create new Experience Cloud site, LWR vs Aura template, set up community portal domain, Experience Builder page builder, branding sets, navigation menu configuration, Microsite LWR, Build Your Own LWR. NOT for coding LWR themes or custom components — use lwc/lwr-site-development. NOT for deploying a finished site to another org — use devops/experience-cloud-deployment-admin. Also covers the deployable metadata: Network, CustomSite, NavigationMenu, ExperienceBundle, DigitalExperienceBundle, urlPathPrefix, networkMemberGroups, emailSenderAddress, site status Live vs UnderConstruction.

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Author the Salesforce Configuration Workbook — the structured, reviewable handoff document an admin uses to execute a feature across Objects/Fields, Page Layouts, Profiles/PSGs, Sharing, Validation, Automation, List Views, Reports, Integrations, and Data. Triggers: 'salesforce configuration workbook', 'admin handoff document', 'implementation workbook'. NOT for object design itself (use admin/custom-field-creation, admin/lookup-and-relationship-design, agents/object-designer/AGENT.md), NOT for permission set design (use admin/permission-set-architecture, agents/permission-set-architect/AGENT.md), NOT for Flow construction (use skills/flow/* and agents/flow-builder/AGENT.md), and NOT for the deployment manifest (use skills/devops/metadata-api-retrieve-deploy). More triggers: workbook row schema, recommended_agent, recommended_skills, row_id, source_req_id, RTM linkage block, not-in-scope-this-release, descope ledger, version-lock the workbook, check_workbook.py.

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Analyze franchise and multi-location unit economics including per-location P&L construction, four-wall EBITDA margins, prime cost optimization, contribution margin analysis, break-even modeling, and store-level ROI calculations.

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Audit real estate investment software for IRR/NPV/cap rate/cash-on-cash return calculations, pro forma income modeling (GPR, vacancy, rent growth, NNN pass-throughs), equity waterfall and promote structures, debt modeling (fixed/ARM/IO/construction loans).

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Audit construction project management software for budget tracking accuracy, earned value management (EVM) formula correctness, risk factor modeling, schedule-cost integration, change order workflow completeness, and early warning detection..

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Run a Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.

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Reconstruct editable LaTeX from PDF content using page-aware extraction and visual comparison. Preserve source evidence, flag uncertain math/tables/citations, and distinguish text extraction, OCR, reconstruction, and verified compilation.

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当AI智能体需要将法律推理结果组织为完整、自洽、有说服力的论证结构时触发此技能。 典型触发场景包括但不限于： - 撰写法律意见书、代理词、辩护词、答辩状等法律文书中的论证部分 - 回答用户提出的复杂法律问题，需要多步骤推理并呈现结论 - 对争议焦点进行系统性分析，需要构建从事实到法律到结论的完整推理路径 - 反驳对方观点时，需要构建替代性论证链条 - 对多个法律问题进行综合分析，需要确保各论证之间逻辑一致、互不矛盾 - 在法律研究备忘录中呈现分析结论 触发信号关键词：论证、分析、推理、为什么、证明、理由、论述、阐述观点、法律分析

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Tune moflo's memory stack for speed, RAM, and index quality. Covers HNSW parameters (M, efConstruction, ef), vector quantization, batch operations, and common bottlenecks. Use when scaling past ~100k entries or when search latency regresses.

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Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold. Includes adversarial review gate, dependency graph, parallel step detection, anti-pattern catalog, and plan mutation protocol. TRIGGER when: user requests a plan, blueprint, or roadmap for a complex multi-PR task, or describes work that needs multiple sessions. DO NOT TRIGGER when: task is completable in a single PR or fewer than 3 tool calls, or user says "just do it".

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Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.

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Professional network graph analyst identifying Gladwellian superconnectors, mavens, and influence brokers using betweenness centrality, structural holes theory, and multi-source network reconstruction. Activate on 'superconnectors', 'network analysis', 'who knows who', 'professional network', 'influence mapping', 'betweenness centrality'. NOT for surveillance, discrimination, stalking, privacy violation, or speculation without data.

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Expert landscape designer transforming yards through photo mapping, 3D visualization, seasonal planning, and deep plant knowledge. Specializes in fast-growing privacy screens (knows arborvitae pitfalls), architecture-appropriate design, outdoor living spaces, and realistic maintenance expectations. Activate on "landscape design", "yard design", "garden planning", "plant selection", "privacy screen", "outdoor living", "backyard makeover", "arborvitae", "hedge", "fast growing tree", "landscaping ideas". NOT for interior design (use interior-design-expert), hardscape construction (consult contractors), or lawn care chemicals (consult local experts).

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