163 件 ・ 関連度順
概要と使いどころ
Synthesize qualitative and quantitative user research into structured insights and opportunity areas. Use when analyzing interview notes, survey responses, support tickets, or behavioral data to identify themes, build personas, or prioritize opportunities.
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Create detailed user personas based on research and data. Develop realistic representations of target users to guide product decisions and ensure user-centered design.
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。
Use when the user asks to "analyze my target audience", "build an audience profile for influencer targeting", "research a niche community", or "deep-dive a subculture before partnering with creators"; in audience mode produces demographic/psychographic profiles, a platform-priority matrix, named personas, and an influencer-selection criteria set, and in niche mode produces a community map, culture decode (language/norms/taboos), key-voice tiers, a Brand Fit Score, and a phased entry strategy. Not for finding specific creators to contract — use influencer-discovery; not for scoring a shortlist on Suitability — use fit-scorer. 目标受众画像/人群分析 · 细分社群/亚文化调研
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 research-grounded personas with goals, frustrations, and behavioural patterns. Use when decisions need a consistent user reference. For one session's emotional snapshot use `empathy-map`; for motivation framing use `jobs-to-be-done`.
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。
Diagnostic-only test suite auditor. Classifies repo type, maps against 7-layer testing taxonomy (git hooks → static → unit → integration → system → E2E → acceptance), runs deterministic quality gates (coverage, mutation, CRAP, architecture, escape-scan), builds RTM / personas / journeys traceability, produces TEST_AUDIT.md, updates tests/TESTING.md, and mandatorily hands off to implement-tests when gaps are found. Use when auditing test quality, finding test gaps, or running the full 7-layer sweep. Trigger with "audit tests", "find gaps", "test audit", "check test quality", "full sweep", "7-layer audit", "rtm check".
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 C4 Context-level documentation specialist. Creates high-level system context diagrams, documents personas, user journeys, system features, and external dependencies. Synthesizes container and component documentation with system documentation to create comprehensive context-level architecture. Use when creating the highest-level C4 system context 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。
AI video conversations - create real-time video calls with AI personas
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。
End-to-end website audit through ICP eyes. Builds synthetic personas (if they don't already exist), runs a structured scorecard review of the client's site, then runs a head-to-head competitive comparison against top competitors. Produces a single consolidated report with persona feedback, competitive positioning, and prioritized recommendations. The complete "how do our buyers actually experience our site vs the competition?" workflow.
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。
Detect buying signals across TAM companies and watchlist personas. Three-phase architecture: (1) free diff-based signals from existing data (headcount growth, tech stack changes, funding rounds), (2) Apify-powered signals (job postings, LinkedIn content analysis, profile changes), and (3) post-processing with dedup, scoring, and lead status updates. Writes signals to Supabase signals table for downstream activation.
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。
5 expert personas debate proposed changes before implementation. Catches architectural, security, performance, and UX issues early. Use before major features or risky changes.
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。
蒸笼：蒸馏任何人的叙事入口——对齐数字永生引擎，强调生活化「蒸」与公开方法论顾问场景；委托上级 kit/personas 执行。
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。
UX research and design toolkit covering persona generation, journey mapping, usability testing, and research synthesis. Use for user research, persona creation, journey mapping, or design validation.
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。
Run a simulated focus group of CRM-grounded personas reacting to messaging or pricing. "run a focus group on this message"
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。
Profile 2-4 buyer personas as narrative documents: drivers, objections, journey. "create a buyer persona"
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。
Research audiences: personas, JTBD maps, RFM segments. One persona doc → audience-profile. "run a JTBD 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。
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。
Negotiate a pre-code contract between generator and evaluator personas that defines what "done" means before any code is written. Turns fuzzy specs into a testable target the evaluator can hold the generator to.
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。
Define a brand's target audience with deep personas, psychographics, and ICP (Ideal Customer Profile). Use when the user says "target audience", "ideal customer", "customer persona", "audience persona", "ICP", "who is our customer", "define our audience", "audience research", "buyer persona", "who should we be targeting", "audience profile", "customer profile", "who buys this", or needs to understand their audience more deeply before investing in brand or marketing work.
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。
Define ideal customer profiles and buyer personas with structured frameworks. Use when the user asks about ideal customer profile, ICP, buyer persona, target audience definition, customer segmentation, customer research, user interviews, or persona creation. Trigger phrases include "ideal customer profile", "ICP", "buyer persona", "who is my customer", "target audience", "customer profile", "persona", "customer segmentation", "user research", "customer interview", "who should I target".
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。
Create clearly labeled fictional personas and consistent dialogue from explicit character attributes. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
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。
Your software-engineering brain trust. Named personas across 11 cells covering cloud architecture, reliability/SRE/observability, data and storage, security, FinOps, languages and runtimes, systems programming, web and frontend…
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Your product + design brain trust and decision partner. Named personas across 8 cells spanning product strategy, discovery/research, growth/metrics, design foundations/usability, design leadership/craft, UX/content, design systems, and a…
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。
Strategy Super Intelligence Team. Named real-world personas across 7 cells. Built local-first (LM Studio) and validator-gated. Illustrative composites; see DISCLAIMER.md.
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。
Your education and edtech brain trust. 25 named personas across 7 cells covering learning science, curriculum design, AI tutoring, higher-ed strategy, edtech platforms, assessment, and workforce development.
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。