「desire」の検索結果

Mine comments and replies on social posts, videos, and ads for recurring customer language, questions, objections, desired outcomes, complaints, product requests, purchase signals, and creative opportunities. Use for voice-of-customer research grounded in linked source evidence.

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CloudBase declarative deployment from a cloudbaserc config (声明式部署, 配置式部署, cloudbaserc 部署) through the deployBuild / deployPlan / deployApply MCP tools. Use when deploying database, functions, app, hosting, or gateway resources described in cloudbaserc.json/yaml as a single desired-state config, when a user wants to build static hosting artifacts locally first (deployBuild), or wants a dry-run plan before applying (deployPlan), or when handling multi-environment deploys via mode / envOverrides. Covers build-plan-apply flow (deployBuild local build → deployPlan dry-run → deployApply confirm=true), hosting build-output neutralization, envId resolution priority, only/skip filtering, concurrency, and continueOnError. Prefer deployBuild (when hosting declares a buildCommand) and deployPlan before deployApply; do not confuse with per-resource tcb CLI deploy or single-function deploy.

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。

Clarify a new customer brief, desired outcome, constraints and evidence gaps. Use for kickoff or a first meeting; do not repeat discovery already supplied.

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 the brand narrative in AI engines against desired positioning, flag misstatements. "is AI misrepresenting our brand"

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。

Design the deeper patterns, structures, artefacts, and mental models needed to grow a desired event. Use when a class imagines a better future.

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 a unit using backwards design from desired outcomes through assessment evidence to learning activities. Use when starting a new unit or redesigning an existing one from standards.

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。

This package provides a collection of functions designed for analyzing deconvolution of the bulk sample(s) using an atlas of reference omic signature profiles and a user-selected model. Users are given the option to create or extend a reference atlas and,also simulate the desired size of the bulk signature profile of the reference cell types.The package includes the cell-type-specific methylation atlas and, Illumina Epic B5 probe ids that can be used in deconvolution. Additionally,we included BS

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Build evidence-backed day trips, multi-day itineraries, and efficient stop sequences with Google Maps data through the standalone CLI. Use when the desired output is a practical travel plan, not merely a route or list of places.

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Viral video replication tool that supports copying popular video structures, scripts, and styles to generate similar content. Use this skill when users mention "viral replication, viral cloning, copy video, clone video, similar video" or express the desire to create content similar to a popular video.

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Use when a problem or issue needs explicit framing before deeper analysis begins — establishing the Problem statement, Current state, Desired state, Stakeholders, and Success criteria. This should trigger when an issue's Problem Framing point of view needs evaluation, or when a maintainer directly asks to frame a problem before root-cause analysis, design, or planning begins. Part of Plinth Toolkit

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When user is asking for guidance for which role to assign to an identity given desired permissions, this agent helps them understand the role that will meet the requirements with least privilege access and how to apply that role.

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Performs a gap analysis between two artifacts (a current state and a desired state) and produces a plain-language, stakeholder-readable report indexed by stable gap IDs. Use when the user wants to compare, evaluate, audit, or reconcile one artifact against another. Does not investigate runtime bugs — use investigate. Does not assess module-level architecture — use architectural-analysis. Does not research open-ended options with no second artifact to compare against — use research.

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Acquisition is expensive. Retention is profitable. Customer success is the discipline of ensuring customers achieve their desired outcomes with your product - which leads to retention, expansion, and advocacy. This skill covers onboarding that activates, health scoring that predicts, retention plays that save, and expansion strategies that grow accounts. Use when "keywords, file_patterns, contexts, " mentioned.

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Calibrated grilling session for stress-testing a plan, design, idea, or decision. First assesses the user's topic knowledge, confidence, and desired pressure level, then asks one question at a time with recommended answers. Use when user says "grill me", "stress-test this", "challenge my plan", "interview me", or wants a plan probed without being overwhelmed.

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Applies the Neoplatonic and mathematical reasoning of Hypatia of Alexandria. Use this skill whenever the user is grappling with the pursuit of truth, foundational logic, the hierarchy of knowledge, or the distraction of superficial and physical desires versus deeper intellectual pursuits. Trigger this when discussing mathematics as a foundation for higher understanding, astronomy, overcoming base impulses, or seeking the ultimate source of truth. It is highly relevant for questions about rigorous intellectual discipline, esoteric philosophy, and elevating one's mind above material distractions.

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。

Identify the pivotal obstacle between current state and desired future. Use when developing strategy.

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 an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to customer opportunities, possible solutions, and experiments. Based on Teresa Torres' Continuous Discovery Habits. Use when the team is unclear what to build next, when multiple opportunities compete, or before writing a PRD for a complex feature space.

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 a unit using backwards design from desired outcomes through assessment evidence to learning activities. Use when starting a new unit or redesigning an existing one from standards.

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。

Design the deeper patterns, structures, artefacts, and mental models needed to grow a desired event. Use when a class imagines a better future.

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。

Simulate pending Sealevel (SVM) warp-route governance txs — signed directly or via a Squads multisig — by forking Solana mainnet locally with surfpool, replaying the exact transactions, then running warp check against the desired registry config. Use to verify that a not-yet-submitted SVM governance change produces the intended on-chain config before it is signed/executed.

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When the user wants to deeply understand their ideal customer before writing copy — pains, desires, inner monologue, and language. Also use when the user mentions "empathy engine", "know your target", "customer pain points", or asks to research their audience before writing Blitz Copy.

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Monitors ArgoCD application sync status via the ArgoCD REST API and gRPC gateway. Detects drift between desired and live Kubernetes manifests and triggers Slack notifications through the Slack Bolt SDK.

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Use when the user brings any fuzzy, half-formed, or interrupt-driven input — an order from a boss, a forwarded email thread, a ticket, a chat message, a "can you look into X", a raw idea — and it needs framing before work starts. Turns the input into a structured brief (Context · Desired outcome · Goal · Owner · Next step · Decision needed). This is the AIOS's front door; run most things through it first. Trigger on "/structure", "frame this", "what's the actual ask here", "structure this", or any vague task that lacks a defined outcome.

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OpenAI GPT Image generation and editing (gpt-image-2, 1.5, 1, mini). Text-to-image, mask-based inpainting, multi-reference composition, multi-turn conversational editing via Responses API, streaming with partial images. This skill should be used when generating or editing images via OpenAI's image models, when near-perfect text rendering in images is needed, when mask-based region-aware editing is required, when multi-turn conversational image editing is desired, or when streaming progressive image delivery is needed. Complements nano-banana-pro (Gemini) as a parallel image generation backend.

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。