「format」の検索結果

Label smarter, not more — pick the most informative examples for annotation to maximize model gains per label.

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。

Master orchestrator for B2B SaaS marketing campaigns using the CATALYST framework (Coordinated Agents for Targeted, Analytics-Led, Year-round SaaS Transformation). Coordinates 90 specialist agents across 17 marketing disciplines. Use this skill for ANY large-scale marketing initiative: full GTM launches, annual marketing plans, multi-channel campaigns, quarterly planning, or any task requiring coordination across content, SEO, paid media, social, email, design, sales enablement, product marketing, analytics, project management, and client operations. Also triggers on: marketing strategy, campaign plan, GTM launch, quarterly plan, marketing ops, full-funnel campaign, marketing audit, growth plan.

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。

Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is "the label's information is not in the features", (3) reviewers propose construct splits (e.g. "designation vs record-evident"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is "partially unpredictable" when the model was simply never shown the document the annotators read.

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。

Build human adjudication / hand-labeling sheets from LLM-pipeline data without evidence truncation. Use when: (1) preparing a CSV/Excel sheet for a human to rule on cases an LLM classifier or rater panel judged, (2) a labeler reports "there is no information to label from" or cells look empty in Excel, (3) excerpt columns cluster at one exact length (e.g. all 1,500 chars — a hard truncation cap). Covers: full rating-basis recovery, Excel 32,767-char cell cap, multi-line CSV mangling, ruling dropdowns, companion text files.

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。

Place pre-screened literature citations into a LaTeX or Word manuscript, or restyle the citations already in one. Three modes: (1) inline placement — inline \cite{}/\citet{}/\citep{} with a compiled references.bib, for author-date journals (APA, MLA, Harvard, Chicago author-date, IEEE, Vancouver); (2) footnote placement — full formatted \footnote{} or OOXML footnotes for legal and notes styles (Bluebook, OSCOLA, Chicago, APA, McGill) with Id./supra short forms; (3) restyle — convert existing footnote citations from one style to another. This skill is manual-invoke ONLY — trigger ONLY when the user explicitly runs /cite-placement or explicitly names the "cite-placement" skill. Do NOT auto-trigger on general citation, footnote, or reference requests.

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。

Plan-aware auto-fix loop after coding. Runs tests, lint, format, and graph checks. Updates plan task status. Use after execute/tdd.

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。

Convert Lanhu HTML/CSS output into project frontend code for Vue, React, or the detected stack, with component reuse and design token mapping.

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。

Brownfield onboarding — audits existing project artifacts for template format compliance (not just existence), classifies gaps by impact, and produces a numbered migration plan. Run this when joining an in-progress project or upgrading from an older template version. Distinct from /project-stage-detect (which checks what exists) — this checks whether what exists will actually work with the template's skills.

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。

Audits game assets for compliance with naming conventions, file size budgets, format standards, and pipeline requirements. Identifies orphaned assets, missing references, and standard violations.

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。

Generates a structured playtest report template or analyzes existing playtest notes into a structured format. Use this to standardize playtest feedback collection and analysis.

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 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 level design-to-code translation. Trigger & event architecture, encounter design contracts, checkpoint & respawn, cinematic & scripted sequences, environmental storytelling hooks, level streaming & loading seams. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/ DESIGN HOOK. 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 data-driven design architecture. ScriptableObject config hierarchies, JSON data pipelines, designer handoff workflows, data versioning and migration, Inspector attributes for self-documenting configs. DECISION format: WHEN/DECISION/SCAFFOLD/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 lifecycle and execution order correctness patterns. Catches common mistakes with initialization ordering, destruction timing, fake-null, disabled components, editor vs runtime init, DontDestroyOnLoad, and async destruction. PATTERN format: WHEN/WRONG/RIGHT/GOTCHA. 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。

Unity game architecture decision patterns. Service Locator vs Singleton vs DI, Event Bus vs ScriptableObject channels, MonoBehaviour vs plain C#, component composition, manager bootstrap sequences. DECISION format: WHEN/DECISION/SCAFFOLD/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 state and behavior system architecture. FSM, Hierarchical FSM, Behavior Trees, stack-based state machines, Animator-vs-code decisions, state machine testing. DECISION format: WHEN/DECISION/SCAFFOLD/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 scene and asset architecture decisions. Additive scene composition, Addressables vs Resources, AssetReference workflow, asset lifecycle coordination, loading screens. DECISION format: WHEN/DECISION/SCAFFOLD/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 query correctness patterns. Catches common mistakes with Raycast, SphereCast, OverlapSphere, NonAlloc allocation, LayerMask construction, trigger interaction, hit ordering, and query type selection. 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 UI/UX pattern design-to-code translation. Screen flow architecture, View/ViewModel separation, HUD architecture, feedback & juice systems, dynamic list/grid views, transition & animation contracts. UI Toolkit only. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. 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 procedural generation design-to-code translation. Noise-based terrain/placement, tile & grid systems, dungeon/room generation, seed & reproducibility, content budget & constraint systems, runtime vs baked generation. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. 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 NPC behavior design-to-code translation. Perception system architecture, decision layer patterns, action execution pipeline, faction & relationship systems, NPC memory & forgetting, crowd & squad coordination. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. 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 async and coroutine correctness patterns. Catches common mistakes with Awaitable double-await, missing cancellation tokens, thread context after BackgroundThreadAsync, coroutine error swallowing, batch mode WaitForEndOfFrame, and Addressables handle leaks. PATTERN format: WHEN/WRONG/RIGHT/GOTCHA. 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。

Unity 3D math correctness patterns. Catches common mistakes with coordinate spaces, Quaternion, Vector3, Plane, Bounds, Transform hierarchies, raycasting projection, and floating-point precision. PATTERN format: WHEN/WRONG/RIGHT/GOTCHA. 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。

MemoryPack high-performance binary serialization for Unity including custom formatters, versioning, and performance patterns.

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。