Run an explicitly requested decision interview and record each settled decision in durable project documentation.
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概要と使いどころ
Run an explicitly requested decision interview and record each settled decision in durable project 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。
Create AI avatar videos with precise control over avatars, voices, scripts, scenes, and backgrounds using HeyGen's v2 API. Use when: (1) Choosing a specific avatar and voice for a video, (2) Writing exact scripts for an avatar to speak, (3) Building multi-scene videos with different backgrounds per scene, (4) Creating transparent WebM videos for compositing, (5) Using talking photos as video presenters, (6) Integrating HeyGen avatars with Remotion, (7) Batch video generation with exact specs, (8) Brand-consistent production videos with precise control.
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When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' 'consumer behavior,' 'anchoring,' 'social proof,' 'scarcity,' 'loss aversion,' 'framing,' or 'nudge.' Use this whenever someone wants to understand or leverage how people think and make decisions in a marketing context. For applying psychology to specific pages, see cro; for pricing tactics, see pricing; for copy framing, see copywriting.
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Supports structured what-if scenario analysis for research planning, experimental contingencies, and scientific project decisions. Explores favorable, reference, adverse, wild-card, contrarian, and second-order scenarios with explicit assumptions, evidence, and decision triggers. Use to stress-test a research plan under uncertainty; scenario narratives do not estimate causal effects or calibrated forecast probabilities.
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Plans, executes, and documents validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.
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Structures a multi-perspective council exercise for decisions, research trade-offs, and creative challenges. Simulates thinking archetypes, separates evidence from assumptions and values, and synthesizes a conditional recommendation. Use when the user requests a council, panel, devil's advocate analysis, "mind council", or deliberate comparison of perspectives on a difficult choice.
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Prepares and validates research-only clinical decision-support evaluation, evidence-profile, cohort, survival, biomarker/model, privacy, and governance artifacts. Supports aggregate or synthetic research documentation and traceability, excluding patient care and live clinical operation.
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Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design.
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。
Triage open herdr GitHub issues into a concise decision-first Markdown table. Use when the user says "triage", asks to triage open issues, asks which issues need attention, or wants issue priority/recommendation lights for herdr.
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Generate concise, actionable meeting minutes for internal meetings. Includes metadata, attendees, agenda, decisions, action items (owner + due date), and follow-up steps.
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Authors a Dynamics 365 Finance and Supply Chain Management Solution Blueprint from scratch through a structured, section-by-section architect interview, establishing scope, target operating model, application and data architecture, integration landscape, migration strategy, security model, ALM, testing, deployment, and support approach, with a decision log capturing rationale and rejected alternatives. Use when the user wants to create D365 implementation architecture documentation, start a D365 implementation, design the architecture, prepare a Solution Blueprint, or identify the architectural decisions the programme must make. Do not use for critique of an existing design; that is a review task rather than blueprint authoring.
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Harbor intake for external work — the captain only handles unresolved decisions. Sweeps incoming issues and PRs, verifies every claim before disposition, reuses every decision already made, and hands the maintainer a docket whose pending items each carry one question with options, recommendation, impact and evidence. Agent-autonomous for facts and for actions covered by standing authorization; signed for every new judgment. Never merges.
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Workflow for upgrading/integrating cache-dit in SGLang diffusion (multimodal_gen): DBCache, DMD calibrator, TaylorSeer, SVDQuant DQ; porting upstream PRs and resolving conflicts against the per-request knob system; adding new cache knobs; building the sglang generate CLI test matrix; precision validation (PSNR / log evidence); troubleshooting environment issues (wheel ABI, svdq extension, flashinfer conflicts). Use when upgrading or integrating cache-dit in sglang diffusion, porting cache-dit PRs with conflicts, adding cache knobs, running the sglang generate CLI test matrix, or validating precision (PSNR) for DBCache/DMD/SVDQuant(DQ) paths.
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Installs and runs the kube-bench tool against a Kubernetes cluster as a Job, DaemonSet, or standalone binary, selecting the correct benchmark version and targets (control plane, etcd, kubelet, worker nodes) and emitting JSON or JUnit output for pipelines. Use when setting kube-bench up for the first time, choosing which benchmark version and node targets to run, wiring it into CI, or troubleshooting skipped or misdetected checks. Keywords: kube-bench, DaemonSet, --benchmark, --targets, JSON output, JUnit, CI integration. Do not use for interpreting the findings or producing an audit report - use performing-kubernetes-cis-benchmark-with-kube-bench.
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。
Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design.
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。
Executive leadership guidance for strategic decision-making, organizational development, and stakeholder management. Includes strategy analyzer, financial scenario modeling, board governance frameworks, and investor relations playbooks. Use when planning strategy, preparing board presentations, managing investors, developing organizational culture, making executive decisions, or when user mentions CEO, strategic planning, board meetings, investor updates, organizational leadership, or executive strategy.
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Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.
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Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2
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Search conversation history and semantic memory to recall previous discussions, decisions, and context. Use when the user asks to "search memory", "what did we discuss", "remember when", "find previous conversation", "check history", or before starting work to recall prior decisions.
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Create or evaluate an architecture decision record (ADR). Use when choosing between technologies (e.g., Kafka vs SQS), documenting a design decision with trade-offs and consequences, reviewing a system design proposal, or designing a new component from requirements and constraints.
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This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".
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。
The session loop that makes agentmemory pay off, recall before starting work, save at decision points, learn from corrections. Use when starting a nontrivial task, after settling a decision or debugging a gotcha, or whenever deciding if something belongs in memory.
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Adversarial thinking partner for founders and executives. Stress-tests plans, prepares for brutal board meetings, dissects decisions with no good options, and forces honest post-mortems. Use when you need someone to find the holes before the board does, make a decision you've been avoiding, or understand what actually went wrong.
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This skill should be used when the user asks to "design system architecture", "evaluate microservices vs monolith", "create architecture diagrams", "analyze dependencies", "choose a database", "plan for scalability", "make technical decisions", or "review system design". Use for architecture decision records (ADRs), tech stack evaluation, system design reviews, dependency analysis, and generating architecture diagrams in Mermaid, PlantUML, or ASCII format.
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。