「cis」の検索結果

Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed.

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Master metrics definition, KPI tracking, dashboarding, A/B testing, and data-driven decision making. Use data to guide product decisions.

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Applies Judea Pearl's causal reasoning frameworks to distinguish correlation from causation, evaluate AI capabilities, and make counterfactual decisions. Reach for this skill whenever Claude encounters questions about causal inference, structural causal models, the limitations of deep learning, AGI, experimental design, covariate selection, or personalized decision-making. Trigger this skill for topics involving Bayesian networks, the do-calculus, the Ladder of Causation, or when a user tries to answer 'what if' or 'why' questions using purely observational data. Pearl's principles are essential for moving beyond probability calculus into true causal understanding.

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Removes unnecessary code from a repository while preserving exactly the behavior exercised by a given test suite. Use this skill when you need to debloat, slim down, or remove unused code from a codebase based on test coverage. The skill analyzes which code elements (files, classes, functions, methods, branches, imports) are exercised by tests, identifies unreachable or unused code, and safely removes it while ensuring all tests continue to pass. Triggers when users ask to remove unused code, debloat based on tests, eliminate dead code guided by test coverage, or slim down a repository to only test-required functionality.

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Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.

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Use when ranking a list of requirements, features, or backlog items using RICE / ICE / MoSCoW / Kano. Built-in decision tree picks the right framework based on data availability and decision context. Output is a transparent matrix, 2×2 Impact/Effort quadrant, and a Sprint allocation proposal. User-invoked only — do NOT auto-trigger. Triggers on "/pm-prioritize", "/prioritize", "приоритизация", "ранжируй бэклог", "RICE-анализ", "prioritize requirements", "RICE", "ICE", "MoSCoW", "Kano", "rank backlog".

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Build a precise, step-by-step action plan before making any code changes. Use this skill whenever the user describes a feature, bug fix, refactor, or any multi-file change. Also use when the user says "plan", "think through", "what would it take", or describes a problem without jumping to code. TRIGGER BEFORE writing any code for non-trivial changes. Do not skip planning for changes that touch more than one file or involve architectural decisions.

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Manages the Morphir knowledge base under kb/ — OKF bundles and concept documents. Use when adding content to a bundle, creating a new bundle, checking the knowledge base for conformance or provenance drift, building or querying its SQLite index, managing intent through its lifecycle, recording or reading architectural decisions as Decision Records, or navigating, searching and listing its bundles, concepts and links.

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Think and work like an expert Biomedical Imaging Scientist. Use when a task calls for Biomedical Imaging Scientist judgment. Reasons from contrast mechanisms, the resolution-SNR-scan-time triangle, and measurement reliability through DICOM/BIDS pipelines, QIBA profiles, phantom QC (ACR, NEMA IQ, Catphan), and blinded central reads (RECIST, RANO, PERCIST) while treating motion, partial volume effects, and cross-scanner harmonization drift as first-class failure modes.

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Protocol for handling ambiguous decisions and missing/conflicting knowledge during code generation, design, and review. Ensures AI surfaces genuine judgment calls with structured options and stops on hallucination risk instead of silently assuming. Use when a decision has multiple valid approaches, when facts are missing or contradictory, when the user asks 'what should we do here?', 'is this a judgment call?', 'should I ask about this?', 'am I guessing here?', 'what are the tradeoffs?', or when deciding between two reasonable architectural or design options. Also composed by molecules to define how judgment calls and clarification requests are surfaced and resolved.

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Generate structured feature specifications through a collaborative product interview. Acts as a senior PM and business analyst pair — arrives with a point of view, challenges scope, proposes options at every decision. Composes the requirement-quality atom for spec quality enforcement and collaborative-judgment for surfacing genuine decisions. Produces an epic/feature hierarchy in .lattice/requirements/ that serves as direct input to design-blueprint. Use when the user says 'forge requirements', 'write requirements', 'spec this feature', 'create a feature spec', 'define this epic', 'write a PRD', 'spec out what we are building', or 'requirement forge'.

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Provider-independent production workflow for creating Manim-based explainer animations. Use when an agent must plan, code, render, QA, or hand off precise math, science, data, diagram, algorithm, or concept animations with Manim, including storyboard, scene architecture, formulas, coordinate systems, voiceover timing, accessibility, reproducibility, provenance, and delivery decisions.

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Provider-independent production guidance for converting observed video into precise, objective, temporally ordered language. Use for shot descriptions, searchable metadata, dataset captions, reference logs, generation-prompt handoffs, and analysis across subject, scene, motion, spatial, and camera aspects; not for deciding what to shoot, accessibility captions, creative interpretation, or provider-specific video analysis APIs.

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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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Detect allele-specific chromatin accessibility from ATAC-seq using WASP, GATK ASEReadCounter, or RASQUAL. Use when mapping cis-regulatory genetic variants from heterozygous SNPs, separating cis from trans regulation, building chromatin QTL (caQTL) maps, validating GWAS variant function with allelic imbalance, or detecting reference allele mapping bias before downstream analysis.

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Create MATLAB Course Designer Simulink Exercise learning activities with starter and solution Simulink model files. Use when the user asks to create a Simulink activity, Simulink Exercise, starter model, solution model, model-based learning activity, or Course Designer-ready Simulink artifact. Uses MATLAB MCP Server tool calls and Simulink Agentic Toolkit guidance to create, inspect, edit, simulate, and validate model files.

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Interview an instructor and generate a complete MATLAB and Simulink enabled course in IMS Common Cartridge format. Use when the user asks to create a MATLAB course, Simulink course, MATLAB and Simulink curriculum, MATLAB Course Designer-ready course shell, Common Cartridge course package, .imscc export, MATLAB Exercises with validated .m files, or Simulink Exercises with starter and solution model files. Coordinates IDStack, MATLAB Agentic Toolkit, Simulink Agentic Toolkit, matlab-create-course-activity, simulink-create-course-activity, and the existing matlab-generate-grader-assessments skill.

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Use when prompting a learner to complete hands-on MATLAB coding exercises, guided practice, debugging drills, code tracing, small MATLAB projects, or MATLAB-script assessment during tutoring. Use when the tutor should create a complete runnable MATLAB script, execute it through MATLAB tools, compare the produced outputs with expected outputs, and evaluate MATLAB programming style.

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Guides God Committee members through consensus-building for collective decisions. Use for proposals, voting, and disagreement resolution. Triggers on: consensus, voting, proposal, committee decision.

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Define how system components connect, establishing boundaries, patterns, and integration approaches during PRD v0.6 Architecture. Triggers on requests to design architecture, create system design, define component relationships, or when user asks "design architecture", "system design", "how do components connect?", "architecture decisions", "technical architecture", "system overview". Consumes TECH- (stack selections), RISK- (constraints), FEA- (features). Outputs ARC- entries documenting architecture decisions with rationale. Feeds v0.6 Technical Specification.

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This skill should be used when the user says "/council", "council", "deliberate", "multi-perspective decision", "트레이드오프 분석", "위원회 소집", "여러 관점으로 검토", or wants deep multi-perspective deliberation with tradeoff mapping. Combines tribunal (structured adversarial review), agent-council (external LLM opinions), dev-scan (community sentiment), and step-back (meta-level review) into a unified decision-making committee. Uses Agent Teams for real peer-to-peer debate with iterative step-back moderation loop.

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Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result). Local by default; commit it when a reviewer needs the trail to trust the result. Use for /show-me-your-work, autonomous or multi-phase runs, or work a human reviews after stepping away.

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Building modular, debuggable AI behaviors using behavior trees for game NPCs and agentsUse when "behavior tree, bt, npc ai, ai behavior, game ai, decision tree, blackboard, ai, behavior-trees, npc, game-ai, decision-making, agents" mentioned.

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Expert in the human side of code review. Covers giving feedback that lands, receiving criticism gracefully, navigating disagreements, and building a healthy review culture. Understands that code review is as much about relationships as it is about code quality. Use when "code review, PR feedback, review comments, how to give feedback, harsh review, review culture, constructive criticism, " mentioned.

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。