「ols」の検索結果

Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire or the AI annex buyers now attach to it, executing sales sequences, coaching qualification, or deciding what the website's AI chat agent is allowed to say. Also triggers on: outbound, cold outreach, reply handling, reply classification, out-of-office replies, auto-replies counted as replies, our reply rate is inflated, prospect replied remove me, opt-out by reply, is this list ready to send, launch readiness, CRM segment outbound, we emailed a current customer, outbound hit an open opportunity, ownerless leads, prospects engaging our competitors, competitor connections, displacement list, is this personalization creepy, can we mention they visited our site, signal freshness, deal strategy, pipeline, battle card, objection handling, common objections, why do we keep hearing this objection, mine call transcripts for objections, objection register, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, AI security questionnaire, AI annex, AI vendor due diligence, the buyer is asking if we train on their data, do you train on customer data, which model do you use, model provider sub-processor, AI subprocessor disclosure, where does inference run, can the customer turn the AI feature off, AI-CAIQ, CSA AI Controls Matrix, ISO 42001, ISO/IEC 42001, NIST AI RMF, EU AI Act Article 50, are we a provider or a deployer, AI feature disclosure, our model vendor changed and nobody told the buyer, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss, website chatbot, chat widget, AI chat agent, AI SDR, inbound AI SDR, conversational marketing, live chat, what should our chatbot be allowed to say, our chatbot quoted the wrong price, the bot promised a discount, do we have to disclose it is AI, EU AI Act chatbot disclosure, chatbot handoff to sales, chat transcript review, prompt injection on our chatbot, Drift, Qualified, Intercom.

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查询蝉镜标签、消耗、价格，管理分片上传或生成创意 Briefing 时使用。需要已配置的蝉镜 OpenAPI AK/SK。

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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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Serena code intelligence — LSP-powered symbol navigation, diagnostics, and targeted code surgery. Activate before complex refactors, cross-file analysis, or when graph tools need symbol-level depth.

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Inject juice and game feel into gameplay code using the project's chosen middleware. Use when adding screen shake, tweens, particles, audio feedback, haptics, hitstop, or any form of "juice" to gameplay events. Triggers on requests like "add juice", "make this feel better", "add screen shake", "polish this feature", "add feedback to this action", "make the hit feel impactful", "add particles when", "screen shake on damage", "tween this", "add camera shake", "make this snappy", or any game feel, polish, or feedback work. Always reads ProjectConfig.yaml -> feel_tools and docs/GFD.md Feedback Matrix before generating code.

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Unity UI patterns including Canvas optimization, list virtualization, and mobile-friendly UI.

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UniTask async/await patterns for Unity including cancellation, lifecycle binding, and coroutine interop.

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VContainer dependency injection patterns for Unity including lifecycle management, scoped registrations, and common pitfalls.

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State machine patterns for Unity including hierarchical states, async transitions, and cleanup safety.

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Unity Test Framework patterns for EditMode and PlayMode tests including async testing, mocking, and test organization.

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Wwise audio middleware integration for Unity including events, banks, RTPC, spatial audio, and callback handling.

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Unity animation patterns including Animancer, state machines, and performance optimization.

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MemoryPack high-performance binary serialization for Unity including custom formatters, versioning, and performance patterns.

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Unity NavMesh pathfinding patterns, safety checks, and performance optimization.

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Object pooling patterns for Unity to reduce GC allocations and improve performance.

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Unity physics patterns including character controllers, collision handling, and tunneling prevention.

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FlowCanvas visual scripting patterns for abilities, custom nodes, and graph execution.

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Unity profiling patterns including ProfilerMarkers, FrameTimingManager, memory profiling, and performance budgets.

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Unity Cinemachine camera system patterns including virtual cameras, blending, and state-driven cameras.

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Sentry Unity SDK integration patterns for error tracking, performance monitoring, transactions, spans, and custom instrumentation.

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Unity Addressables patterns for asset loading, memory management, reference counting, and remote content delivery.

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Gameplay Ability System patterns for abilities, effects, attributes, and tags including recursion safety and lifecycle management.

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Behavior Designer patterns for AI behavior trees including task creation, shared variables, conditionals, and debugging.

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Unity 6 Input System guide. Use when handling player input, controls, gamepad, keyboard, mouse, touch, or XR controllers. Covers the new Input System package (recommended), Input Actions, Action Maps, Control Schemes, PlayerInput component, and input debugging. Based on Unity 6.3 LTS documentation.

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