3.2천건 · 관련도순
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,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Writes the character-performance layer of a video prompt as behavior under pressure, not displayed emotion — objective, obstacle, tactics, beats, subtext, listening, body/status/proxemics, and mandatory eye life. Produces a reusable 150–220-word acting master profile per character plus a per-scene rewrite of it, and a locked voice prompt. Use whenever a prompt needs acting, performance, or emotion direction; whenever characters read wooden, dead-eyed, or 'AI'; whenever a character must stay themselves across many shots; or when the user asks for character behavior, mannerisms, tics, a gait, or how someone reacts. Pairs with higgsfield-facs (muscle-level AU codes) and higgsfield-seedance (the prompt the paragraph goes into).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when the user asks about "ralph arguments", "quick mode", "commit spec", "max iterations", "ralph state file", "prototype overlay", "execution modes", "ralph loop", "coordinator behavior", "delegate to subagent", or needs guidance on Ralph plugin arguments, state management, delegation patterns, or execution loop behavior. Core behavioral skill for all Ralph Specum operations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Provides patterns for unit testing Spring `@Scheduled` and `@Async` methods using JUnit 5, CompletableFuture, Awaitility, and Mockito. Covers mocking task execution and timing, verifying execution counts, testing cron expressions, validating retry behavior, and simulating thread pool behavior. Use when testing background tasks, cron jobs, periodic execution, scheduled tasks, or thread pool behavior.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Automatically updates a codebase to a new language version, framework version, or library update while ensuring all tests still pass. Use this skill when migrating Python 2→3, upgrading framework versions (React, Django, Angular), updating dependencies, or performing any version migration where tests define correct behavior. The skill analyzes failing tests caused by migration, categorizes errors (import errors, API changes, type errors, behavior changes), proposes systematic fixes, and verifies that test-observable behavior remains unchanged. Triggers when users ask to migrate code versions, upgrade dependencies while keeping tests passing, update framework versions, or perform test-guided version migrations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Checks whether a new version of a repository preserves the behavior observed by tests on the old version. Use this skill when comparing two versions of code to detect regressions, verify refactoring safety, validate bug fixes don't break existing functionality, or ensure backward compatibility. Detects differences in function outputs, exceptions, observable states, and performance between versions. Generates reports highlighting potential regressions (critical, high, medium, low severity), improvements, and areas requiring verification. Triggers when users ask to check for regressions between versions, compare test behavior across versions, verify behavior preservation, or validate that changes don't break existing tests.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyzes and verifies semantic equivalence between two functions, classes, or modules by examining control flow, data flow, and observable behavior. Use when comparing code implementations (refactored vs original, different implementations of same functionality, migration verification), determining if two code artifacts produce identical behavior, identifying behavioral differences between code versions, or validating that code changes preserve semantics. Supports formal reasoning and symbolic execution approaches.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Think and work like an expert Behavioral Ecologist. Use when a task calls for Behavioral Ecologist judgment. Reasons from versioned ethograms, Altmann focal/scan sampling, and activity budgets; scores with BORIS (Cohen’s κ), analyzes sequences with Markov/HMM tools, runs sham-controlled playbacks under ARRIVE 2.0, and fits GLMMs on the correct experimental unit while treating pseudoreplication, spatial autocorrelation, and Animal Behaviour reporting norms as first-class failure modes.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Think and work like an expert Behavioral Neuroscientist. Use when a task calls for Behavioral Neuroscientist judgment. Reasons from contingency structure, deprivation state, and latent arousal/motivation variables through Morris water maze, contextual/cued fear conditioning, operant schedules on Med Associates rigs, and DeepLabCut/SLEAP/SimBA tracking validated against ethograms, while treating thigmotaxis-as-anxiety, locomotor confounds of memory deficits, peripheral CNO sedation, and trials-as-n pseudoreplication as first-class failure modes.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Investigate unexpected behavior and mysterious bugs. Use when the cause of a problem is unknown and the user needs to understand WHY something is happening — symptoms like: sudden unexplained changes in metrics or behavior, works locally but not in staging/production, inconsistent or intermittent failures, correct code producing wrong results, operations succeeding but having no effect, environment-specific failures, duplicate executions, stale data, or any "why did this change?" or "why is this happening?" situation. Covers infrastructure anomalies (cache hit rates dropping, latency spikes, queue behavior shifts) as well as code bugs. The key signal is confusion about root cause, not a request to implement a known fix. Do NOT use for feature requests, known fixes, planning, or documentation tasks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
"Apply behavioral finance theory to identify systematic investor biases and their impact on asset prices. Use this skill when the user needs to analyze irrational market behavior, explain pricing anomalies through cognitive biases, diagnose investor decision errors, or when they ask 'why do investors hold losers too long', 'how does loss aversion affect pricing', or 'what biases drive this market pattern'.".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
"Apply behavioral economics concepts including bounded rationality, prospect theory, mental accounting, and nudge theory to analyze decision-making biases. Use this skill when the user needs to understand why people make irrational economic decisions, design choice architectures, or apply nudges to influence behavior — even if they say 'why do customers make bad choices', 'how do we encourage people to save more', or 'design a better default option'.".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Behavior Designer patterns for AI behavior trees including task creation, shared variables, conditionals, and debugging.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when restructuring existing frontend code while preserving observable behavior, including responsibility extraction, module movement, conditional simplification, API cleanup, or data organization. Do not use for new feature behavior, behavior-changing bug fixes, dependency or framework migrations, or proven dead-code cleanup.
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Debug a bug or unexpected behavior systematically. Use when the user says "there's a bug", "this isn't working", "I'm getting an error", "help me debug", "why is this failing", "unexpected behavior", "test is failing", "something is broken", or describes behavior that doesn't match expectations - even if they don't say "debug".
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Analyze behavioral segmentation systems for RFM scoring, cohort tracking, churn propensity, engagement scoring, persona clustering, and journey mapping using behavioral economics frameworks..
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Load this skill when writing, reviewing, or interpreting behavioral accessibility automation — tests that manipulate a rendered page (resizing the viewport, pressing real keys, capturing and comparing screenshots) rather than only inspecting static markup or a single computed accessibility tree. Covers Reflow risk (SC 1.4.10) and Focus Visible risk (SC 2.4.7) checks. Absolutely always report indicator results separately from confirmed failures. Under no circumstances treat a clean behavioral scan as WCAG conformance, or collapse `cantTell`/test-error/indicator outcomes into a single pass/fail signal.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning models to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs. Activates for requests involving authentication anomaly detection, login behavior analysis, UEBA implementation, or suspicious sign-in investigation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Behavioral activation for depression: Breaking the vicious cycle, activity monitoring, weekly planning, and values-based activities.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use test-driven development for behavior-changing feature or fix work, and whenever the user mentions TDD, test-first, red-green-refactor, tracer bullets, integration tests, or public-interface behavior tests. Skip for docs-only, path-only rename, formatting-only, or purely mechanical chores unless explicitly requested.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.