「progress」の検索結果

Comprehensive weekly review of goals, progress, and recommendations

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。

Track and report on progress toward defined goals

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。

Signup and registration flow optimization covering SSO strategy, progressive profiling, field reduction, multi-step flow design, authentication UX, post-submit experience, and mobile registration 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。

Show DMP status for the active brand: profile, engagement progress, recent insights. "what brand am I on"

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。

Draft matter status reports from emails, call notes, and updates. Internal and client-facing formats, RAG logic, variance commentary, escalation flags. Use when asked to draft a status report, write a project update, summarise matter progress, prepare a client report, create a weekly or monthly update, convert emails into a status summary, or produce any kind of matter reporting. Also triggers when the user pastes email threads and asks what the status is, or needs to turn internal updates into client-facing reports.

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。

Framework for demonstrating AI capabilities in legal contexts. Provides detailed personas across tenant law, business contracts, startup disputes, employment claims, and consumer protection with progressive complexity scenarios. Use when: (1) Demonstrating AI-powered legal triage or intake systems, (2) Showcasing responsible AI-assisted client interactions, (3) Training staff on appropriate AI use in legal contexts, (4) Creating realistic scenarios for legal tech presentations, (5) Developing educational materials about AI in legal services, or (6) Testing AI-powered legal information systems in controlled environments.

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。

Matter budgeting and ongoing WIP/variance monitoring. Build phase-based fee estimates at matter setup, run bottom-up budgets by jurisdiction or workstream, calculate contingency, and structure AFA arrangements (fixed fee, capped fee, phased fixed fees). Ongoing monitoring: WIP tracking against budget, proportionality assessment (spend vs progress), variance commentary with root cause analysis, forecast-to-complete, realisation monitoring, write-off analysis. Trigger on: 'build a budget', 'fee estimate', 'what will this cost', 'WIP review', 'budget vs actual', 'how are we tracking against budget', 'we're over budget', 'realisation is poor', 'what's our ETC', 'budget for the German workstream', 'model the financial impact of this scope change', 'draft a fee adjustment', 'write-off analysis', 'how much contingency', 'AFA structure', 'fixed fee estimate', 'budget update', 'forecast to complete'.

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。

A switch whose knob springs across on toggle — a tactile, satisfying on/off state change. Use for settings/form switches. Honors prefers-reduced-motion (quick linear slide). Trigger on user intent only; keep the spring subtle — never to convey loading/progress.

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。

An animated step indicator fills as you advance — clear progress for a multi-step flow (checkout, onboarding). One per flow. Under prefers-reduced-motion fills without easing.

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。

A soft progressive blur fades content out toward an edge — a premium "more below" affordance for a scrolling list/section. Keep the readable content above the blur. Degrades gracefully where backdrop-filter is unsupported.

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。

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

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。

Provide graduated assistance from abstract conceptual nudge to concrete procedural step, with reflection required before each escalation. Teaches help-seeking as a skill and prevents direct-answer shortcuts.

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。

Generate a cascading hint sequence for a problem type, revealing progressively without giving answers. Use when designing tutoring dialogues or scaffolded worksheets.

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。

Authors or reviews Know/Understand/Do charts for competency-based learning targets across developmental bands. Handles seven input types from raw curriculum documents to existing LT sets. Routes to upstream skills when stronger inputs are available.

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。

Expert blueprint for save/load systems using JSON/binary serialization, PERSIST group pattern, versioning, and migration. Covers player progress, settings, game state persistence, and error recovery. Use when implementing save systems OR data persistence. Keywords save, load, JSON, FileAccess, user://, serialization, version migration, PERSIST group.

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。

Expert blueprint for quest tracking systems (objectives, progress, rewards, branching chains) using Resource-based quests, signal-driven updates, and AutoLoad managers. Use when implementing RPG quests or mission systems. Keywords quest, objectives, Quest Resource, QuestObjective, signal-driven, branching, rewards, AutoLoad.

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。

Expert blueprint for RPG stat systems (attributes, leveling, modifiers, damage formulas) using Resource-based stats, stackable modifiers, and derived stat calculations. Use when implementing character progression OR equipment/buff systems. Keywords stats, attributes, leveling, modifiers, CharacterStats, derived stats, damage calculation, XP.

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。

Comprehensive blueprint for Action RPGs including real-time combat (hitbox/hurtbox, stat-based damage), character progression (RPG stats, leveling, skill trees), loot systems (procedural item generation, affixes, rarity tiers), equipment systems (gear slots, stat modifiers), and ability systems (cooldowns, mana cost, AOE). Based on expert ARPG design from Diablo, Path of Exile, Souls-like developers. Trigger keywords: action_rpg, loot_generator, rpg_stats, skill_tree, hitbox_combat, item_affixes, equipment_slots, ability_cooldown, stat_scaling.

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。

Expert blueprint for educational games including gamification loops (learn/apply/feedback/adapt), progress tracking (student profiles, mastery %), adaptive difficulty (target 70% success rate), spaced repetition, curriculum trees (prerequisite system), and visual feedback (confetti, XP bars). Use for learning apps, training simulations, or edutainment. Trigger keywords: educational_game, gamification, adaptive_difficulty, spaced_repetition, student_profile, curriculum_tree, mastery_tracking.

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。

Expert blueprint for survival games (Minecraft, Don't Starve, The Forest, Rust) covering needs systems, resource gathering, crafting recipes, base building, and progression balancing. Use when building open-world survival, crafting-focused, or resource management games. Keywords survival, needs system, crafting, inventory, hunger, resource gathering, base building.

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。

Expert collection-loop systems for collectible IDs, scavenger hunts, completion archives, nearest-item compass UI, hidden spawners, and persistent find-all-X progress. Use when implementing collectibles, scavenger hunts, completion% archives, or compass-guided item hunts. Keywords: collectible_id, scavenger_hunt, collection_manager, collection_compass, completion_archive, hidden_item_spawner, find_all, collectible_item.

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。

Expert blueprint for platformer games including precision movement (coyote time, jump buffering, variable jump height), game feel polish (squash/stretch, particle trails, camera shake), level design principles (difficulty curves, checkpoint placement), collectible systems (progression rewards), and accessibility options (assist mode, remappable controls). Based on Celeste/Hollow Knight design research. Trigger keywords: platformer, coyote_time, jump_buffer, game_feel, level_design, precision_movement.

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。

Data-driven resource harvesting (mining, logging, foraging) for Godot 4: apply_hit tool/tier validation via HarvestToolData enums, HarvestResourceData yields, harvestable_node shake/deplete, respawn_manager world persistence, UNIX offline progress, autosave, and noise vein proc-gen. Trigger keywords: apply_hit, HarvestResourceData, HarvestToolData, offline UNIX, respawn_manager, tool tier, harvestable_node, FastNoiseLite veins.

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。

Expert patterns for RPG/action ability systems including cooldown strategies, combo systems, ability chaining, skill trees with prerequisites, upgrade paths, and resource management. Use when implementing unlockable abilities, character progression, or complex skill systems. Trigger keywords: PlayerAbility, AbilityManager, cooldown, SkillTree, SkillNode, prerequisites, can_use, execute, ComboSystem, ability_chain, global_cooldown, charge_system, upgrade_path.

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。