'structural' 검색 결과

"Apply Granovetter's embeddedness theory to analyze how economic behavior is embedded in ongoing social relations, avoiding both over-socialized and under-socialized accounts. Use this skill when the user needs to explain why market transactions deviate from pure economic rationality, analyze how trust and social ties shape business dealings, evaluate structural vs relational embeddedness in inter-firm networks, or when they ask 'why do firms prefer existing partners over cheaper alternatives', 'how do social relationships shape economic outcomes', or 'is this market truly arms-length'.".

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"Apply organizational ecology (Hannan and Freeman) to analyze population-level dynamics of organizational founding, failure, and selection. Use this skill when the user needs to explain industry-level patterns of birth and death rates, analyze structural inertia and liabilities of newness or aging, evaluate why adaptation is rare relative to selection, or when they ask 'why do most startups fail', 'why is this industry dominated by old firms', or 'why do organizations resist change despite environmental pressure'.".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Split documents for retrieval effectively — fixed, semantic, structural, and hierarchical chunking with overlap tuning. Use when RAG retrieval quality depends on how documents are divided.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Structural and functional brain connectivity — tractography, functional networks, and graph-theoretic analysis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when doing structural code search and rewriting - ast-grep linting, refactoring, multi-language patterns

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Dry-run Trust Magnitude for proposed named skills or suites before curation. Use when deciding whether a proposed suite deserves A/S treatment, when checking Fusion Score structural inputs, when comparing repo stars vs suite component counts, or when asked to appraise a candidate before adding it to the registry.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Simplifies and refines code for clarity, consistency, and maintainability while preserving all functionality. Focuses on recently modified code unless instructed otherwise. This skill should be used when code-quality checks pass but the code would benefit from structural cleanup — deduplication, branching simplification, naming improvements, or dead-code removal. Invoked as a subagent from /code-quality or directly via the Task tool.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Identifies a sample's true file type independent of its extension: matching magic bytes and structural signatures, detecting container/archive formats, and flagging extension-content mismatches used to disguise malware. Activates for requests to identify a file type, check magic bytes, or detect a disguised/spoofed extension.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when a task needs the judgment of a manuscript or content editor — diagnosing structural problems in a draft, writing a developmental edit letter, running a line-edit or copyedit pass, deciding what to cut to hit a word-count target, or triaging conflicting author feedback.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when a task needs the judgment of a Biochemist — determining enzyme kinetics (Km/Vmax, inhibition mechanism) from rate data, choosing a structural-biology method (X-ray crystallography, cryo-EM, or NMR) for a target, designing or interpreting a binding assay (ITC, SPR, fluorescence polarization), or selecting a protein-purification strategy and diagnosing why a prep failed.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when a task needs the judgment of an auto-body-repairer — deciding whether a damaged structural component gets pulled or replaced, reconciling an insurance estimate against actual teardown damage, writing a supplement, determining whether a repair triggers ADAS recalibration, or checking a proposed repair against an OEM position statement.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when a task needs the judgment of a professional author — drafting or structurally revising a novel or narrative-nonfiction manuscript, writing a query letter or book proposal, evaluating a publishing contract's royalty and rights terms, or diagnosing why a manuscript is getting rejected.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when a task needs the judgment of an Aerospace Engineer — reconciling a vehicle mass/weight budget against a certification limit, computing a structural margin of safety, choosing a means of compliance for an FAA certification basis, tracing a weight-growth overrun back to a design decision, or evaluating a propulsion/aerodynamics tradeoff against a range or payload requirement.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Validate skill files for structural compliance and behavioral correctness. Three modes: static (linter), spec (behavioral), audit (coverage report).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when diagnosing structural maintainability problems in existing frontend code before deciding how to refactor it, especially when evidence, false-positive checks, and candidate transformations are needed without editing business code.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when proving that a frontend refactoring preserved existing behavior, selecting an appropriate safety net, validating each structural step, or assigning a PASS, PARTIAL, or NOT PROVEN preservation verdict.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when selecting or composing behavior-preserving refactoring techniques after structural evidence is known, especially when multiple candidate transformations, preconditions, or ordering choices must be compared.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Restructure code while preserving behavior. Use for extraction, consolidation, ownership moves, or cleanup where verification must bracket structural edits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Timeboxed ideation on a topic where lens-driven proposers generate structurally different ideas, blind critics cull them, and pairwise judges rank the survivors on a tournament ladder instead of 1-10 scores, evolving the leaders until the clock runs out. Use when the user wants to brainstorm, explore ideas, discover features, generate options, or think through possibilities for a specified duration. Triggers on requests like "brainstorm X for 30 minutes", "ideate on X", "spend an hour thinking about X", "what features should we build", "explore options for X". Not for executing a task over time (timeboxed-iterating) or optimizing a measurable metric (autoresearch).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create a bounded, extractive, structurally idempotent rollup of recent Obsidian wiki log entries, with dry-run preview by default and one optional transaction apply. Use for manual log compression without modifying child pages. Triggers: fold the log, run a fold, run wiki-fold, log rollup, roll up log entries, commit the fold.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Pre-landing PR review. Analyzes diff against main for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create and own the master game design document (GAME.md — the authored one-pager plus the generated [gen] system/flow maps) and the GD-IDS.yaml facts registry — the top-level, big-picture layer of the GDD and the machine interface the code side reads. Use it to write the master spec from a concept or dialogue, import an existing GDD (a file path or URL), edit GAME.md content ("change a pillar", "rework the monetization stance", "tweak the loop stack"), pitch the game ("pitch" → PITCH.md), re-decompose the systems ("remap"), and — importantly — to add a new system to the design map ("let's add a new system", "add a crafting system to the game design", "add this to the GDD"). This is the structural, map-level layer plus GAME.md content edits. To write or fill in the detailed parameters of one existing system, use /unikit-gd-system; to apply one edit spanning several zones at once use /unikit-gd-apply; to invent a brand-new game concept use /unikit-gd-brainstorm.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Proactive bug-hunting workflow. Assesses codebase risk through complexity, coverage, and structural analysis, then spawns focused investigators that write reproducing tests to validate suspected bugs. Thoroughness over speed. Advisory only — produces findings and proposes tickets; does not implement fixes.

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