「control」の検索結果

Craft effective AI image prompts with structured syntax, style control, and iterative refinement techniques.

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Manage fleets of local AI agents: lifecycle, monitoring, task assignment, and resource control. Use when running multiple CLI agents via an orchestrator like AI Maestro.

日本語の概要は準備中です。原文の説明を表示しています。

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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Reviews VST3 plugin implementations for spec compliance, host compatibility, and correctness. Use when the user asks to review a VST3 plugin, check bus arrangements, audit parameter handling, or verify their process() callback is safe. Trigger on phrases like "review my VST3 plugin", "check VST3 bus arrangement", "is my VST3 process safe", "audit my IAudioProcessor", or when you see IComponent, IAudioProcessor, IEditController, ProcessData, or Vst:: namespaced types in the code.

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pyfixest demeaner_backend="cupy64" (including its CPU fallback when cupy is absent) is NOT numerically identical to the default numba backend and does NOT drop fully-absorbed/collinear regressors the same way. Use when: (1) adding demeaner_backend="cupy64" to existing pf.feols/fepois calls changes the printed coefficient table, (2) a regression report suddenly gains rows with absurd estimates (e.g. coef 435.8, SE 7106) for controls absorbed by the fixed effects, (3) diffing outputs before/after a backend change, or (4) anything parses a pyfixest text report by line position.

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Opt-in DI architecture using Reflex for Unity 6+. Covers container setup, scoping, injection, command pattern, update management, and class taxonomy. Use when ProjectConfig.yaml -> architecture_pattern is "di-first", or when the user asks about dependency injection, inversion of control, service architecture, or testable game code. Triggers on "set up DI", "add dependency injection", "create a service", "wire up dependencies", "make this testable", "decouple these systems", "add a command pattern", "cross-feature communication", or architecture discussions involving testability, decoupling, and service layers. Only activates when ProjectConfig.yaml -> architecture_pattern is "di-first". For simpler projects, use uw-scriptable-object-arch instead.

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Interface-based state machine patterns for Unity game states, character controllers, and UI flows. Use when implementing game flow (menu -> gameplay -> game over), character states (idle -> run -> jump -> fall), AI behavior states, or UI screen transitions. Triggers on "state machine", "game states", "character states", "screen flow", "game flow", "add states to", "idle/run/jump", "menu flow", "AI states", "boss phases", or any task involving managing discrete states with transitions between them. Reads ProjectConfig.yaml -> architecture_pattern to adapt patterns for SO-first or DI-first.

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Break a single epic into implementable story files. Reads the epic, its GDD, governing ADRs, and control manifest. Each story embeds its GDD requirement TR-ID, ADR guidance, acceptance criteria, story type, and test evidence path. Run after /create-epics for each epic.

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Read a story file and implement it. Loads the full context (story, GDD requirement, ADR guidelines, control manifest), routes to the right programmer agent for the system and engine, implements the code and test, and confirms each acceptance criterion. The core implementation skill — run after /story-readiness, before /code-review and /story-done.

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After architecture is complete, produces a flat actionable rules sheet for programmers — what you must do, what you must never do, per system and per layer. Extracted from all Accepted ADRs, technical preferences, and engine reference docs. More immediately actionable than ADRs (which explain why).

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Unity 6 XR development guide. Use when building VR, AR, or MR experiences. Covers XR Interaction Toolkit, XR Plug-in Management, OpenXR, hand tracking, controllers, haptics, AR Foundation (plane detection, anchors, image tracking), and platform-specific setup (Meta Quest, Apple Vision Pro). Based on Unity 6.3 LTS documentation.

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Unity New Input System correctness patterns. Catches common mistakes with action reading (triggered vs IsPressed vs WasPressedThisFrame), action map switching, rebinding persistence, InputValue lifetime, PassThrough vs Value, local multiplayer device assignment, and control scheme auto-switching. PATTERN format: WHEN/WRONG/RIGHT/GOTCHA. Based on Unity 6.3 LTS.

日本語の概要は準備中です。原文の説明を表示しています。

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

日本語の概要は準備中です。原文の説明を表示しています。

Unity 6 animation system guide. Use when working with Animator Controllers, animation state machines, blend trees, animation clips, Avatar system, humanoid rigs, root motion, animation events, Timeline, or Cinemachine. Based on Unity 6.3 LTS documentation.

日本語の概要は準備中です。原文の説明を表示しています。

保持行为的前端重构主要涉及条件控制类重构，已经选定或正在评估对应手法，需要查询该 family 的操作步骤、风险与 JavaScript/TypeScript/React/Vue 适配时。

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Use when behavior-preserving frontend refactoring focuses on conditional complexity, repeated branches, guards, special cases, or internal invariants, and the selected technique needs family-specific mechanics, risks, and JavaScript/TypeScript/React/Vue adaptation.

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Use when building or reviewing substantial forms with React Hook Form, Zod schemas, typed validation, dynamic fields, controlled third-party inputs, file upload, multi-step flows, dependent validation, or form performance. Do not use for trivial 1-3 field forms without validation; Chinese triggers include form, form validation, dynamic fields.

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OpenUI generative UI with a Ruby on Rails backend. SSE streaming via ActionController::Live, forwarding the OpenAI API stream with Net::HTTP.

日本語の概要は準備中です。原文の説明を表示しています。

Ableton Live Object Model (LOM) API reference for Python Remote Scripts and control surface development.

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Use when a task needs the judgment of an Epidemiologist — investigating a disease outbreak and identifying its source, designing a case-control or cohort study to test an exposure hypothesis, calculating attack rates/odds ratios/relative risk from surveillance data, evaluating whether a surveillance system is sensitive and timely enough to catch a real signal, or judging whether an observed case cluster is a true outbreak or expected background variation.

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Use when a task needs the judgment of an Environmental Restoration Planner — screening or comparing CERCLA/RCRA remedial alternatives against the nine evaluation criteria, building a life-cycle cost estimate for a Feasibility Study, scoping a stream or wetland restoration design against a reference reach, sizing compensatory mitigation credits, drafting a Statement of Work or Remedial Action Work Plan, or scoping a Five-Year Review for a site with land-use controls in place.

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Use when a task needs the judgment of an embalmer — assessing a case's decomposition stage and preservation difficulty, calculating an arterial-fluid dilution ratio for a specific case condition, choosing a restorative-art approach for trauma or discoloration, or working through a bloodborne-pathogen exposure-control decision.

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Use when a task needs the judgment of a rotary drill operator (driller) — diagnosing a drilling break or kick warning sign, running well-control shut-in and kill-mud-weight calculations, setting trip margin and swab/surge limits before pulling out of hole, optimizing weight-on-bit and RPM against mechanical specific energy, or reviewing a rig-floor near-miss.

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Use when a task needs the judgment of a drywall and ceiling tile installer — specifying a fire-rated wall/ceiling assembly to a UL design number, hitting an STC target on a demising wall, choosing board type for a wet area, placing control joints on a long run, or diagnosing why a finished assembly failed inspection or a sound/mold complaint.

日本語の概要は準備中です。原文の説明を表示しています。