「tar」の検索結果

Design MVPs, validated learning experiments, and pivot-or-persevere decisions using Build-Measure-Learn. Use when the user mentions "MVP scope", "validated learning", "pivot or persevere", "vanity metrics", "test assumptions", "innovation accounting", "build-measure-learn", "minimum viable experiment", "should we pivot", "test a business idea cheaply", or "build the smallest version first". Also trigger when deciding what to include in a first version, measuring startup progress, or evaluating whether to change direction on a product bet. Covers innovation accounting and actionable metrics. For 5-day prototype testing, see design-sprint. For customer motivation analysis, see 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。

Build a complete marketing plan covering the full customer journey from stranger to raving fan. Use when the user mentions "marketing plan", "marketing strategy", "target market", "USP", "lead nurture", "customer lifetime value", "PVP Index", or "I dont know where to start with marketing". Also trigger when building a marketing plan from scratch, choosing acquisition channels, or designing end-to-end customer-lifecycle campaigns. Covers the PVP Index, channel selection, and advocacy systems. For brand messaging, see storybrand-messaging. For conversion optimization, see cro-methodology.

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。

Guided journey from a business with lucky months to a repeatable growth engine that produces a forecast. Orchestrates nine skills phase by phase - one-page-marketing, hundred-million-offers, predictable-revenue, contagious, influence-psychology, crossing-the-chasm, cold-start-problem, lean-analytics, negotiation - asking the user questions at every decision point and recording results in the project docs/ folder (MARKETING.md, OFFER.md, METRICS.md, GROW-BUSINESS-PLAN.md) so the journey resumes across sessions. Use when the user wants to build a marketing and sales system, manufacture predictable pipeline, engineer word-of-mouth and referrals, or says 'revenue is real but lumpy and I need growth that repeats'. If the offer, retention, or operations underneath are broken, run improve-business first; with no paying customers yet, start with create-business; when the product itself must carry the growth loops, use grow-app. For one framework in isolation, invoke that skill directly.

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。

Deep cultural adaptation of an already translated blog post for one target market: local examples, CTAs, legal references, statistic sources, and formality (Sie/du, tu/vous). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets. Use when the user says "localize blog", "cultural adaptation", "adapt for Germany", "lokalisieren", "localiser", "adaptar" and a translation already exists. Not for translating (use blog-translate), auditing a folder of translations (use blog-locale-audit), or the full write-translate-localize pipeline (use blog-multilingual).

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 a content brief for ONE planned post: target and secondary keywords, search intent, template choice, competitor gaps from the live SERP, sourced statistics to include, section plan, internal-link targets, and distribution ideas. Use when the user says "content brief", "blog brief", "SEO brief", "article brief". Not a skeleton only (blog-outline), a multi-post plan (blog-strategy, blog-calendar, blog-cluster), or the article itself (blog-write).

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。

Cultural adaptation for translated content. Run AFTER blog-translate completes. Adjusts brand examples, CTAs, legal references, and formality for the target market (German, French, Japanese, Spanish, etc.). Deep cultural adaptation of translated blog posts. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets, plus a custom-locale template. Makes content feel locally authored, not translated. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "adapt for France", "lokalisieren", "localiser", "adaptar".

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 detailed content briefs for blog posts with target keywords, content outlines, competitive analysis, recommended statistics, image and chart suggestions, word count targets, internal linking architecture, template recommendations (12 types), TL;DR drafts, citation capsule planning, information gain prompts, and multi-channel distribution plans. Briefs are optimized for Google rankings and AI citation visibility as part of SEO. Use when user says "content brief", "blog brief", "write brief", "SEO brief", "article brief", or "content requirements".

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。

Package, publish, and distribute DeepSeek Harness (DSH) plugins — npm pack artifact validation, GitHub/npm/hub release-track selection, tarball overrides installs for the unpublished cohort (0.1.2-alpha.*), and CI/release gates with rollback. Use when publishing a plugin, packing a tarball, wiring a plugin into a profile/hub, or installing an alpha version that is not on npm; show a plan and obtain user confirmation before any publish action.

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 inference on Fireworks AI — direct, through the Leanmcp AI Gateway proxy (aigateway.leanmcp.com) for observability, or via LiteLLM / the OpenAI SDK / raw HTTP. Covers the endpoint-and-key matrix for each route, serverless vs dedicated deployments and their cold starts, browsing and filtering the model catalogue, reasoning models that return content:null with the answer in reasoning_content, function calling, concurrency and load testing, and runner scripts where many models share one protocol with a --use-proxy toggle. Use this skill whenever the user mentions Fireworks, FIREWORKS_API_KEY, api.fireworks.ai, fireworks_ai/ model ids, accounts/fireworks/models/..., a Fireworks deployment id, the Leanmcp gateway or LEANMCP_API_KEY, app.leanmcp.com observability, or gpt-oss / kimi / glm / qwen / deepseek served on Fireworks; wants to route LLM calls through a proxy for logging or cost tracking; is debugging empty responses, 404s, scope errors, cold starts, or "the gateway isn't working"; wants to pick a Fireworks model with tool calling; or wants to sweep several models over one benchmark. Reach for it even on vague asks like "why is this model returning nothing" or "set up inference for these models" when Fireworks is in play.

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。

Defines and manages service levels — setting targets that reflect what customers need, measuring honestly, and handling breaches. Use this to write or negotiate an SLA, decide what to measure and at what threshold, respond to a missed service level, or work out why a service that meets its targets still has unhappy customers.

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。

Navigate browser to specified URL to open a webpage. When you need to open webpages or start web automation. PREREQUISITE - must call before browser_click/type operations. Auto-starts browser if not running.

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。

Rewrite drafts according to target writing style or target journal format. Triggers when user says "rewrite in XX style", "match this tone", "format for XX journal", "rewrite following this format". Input can be .docx / .md / .txt or conversation text.

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 complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk review.

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 complete comparative network-toxicology research designs from a user-provided exposure pair, shared toxic phenotype, and validation direction. Use when a study centers on two related exposures under one outcome and needs target collection, shared-vs-specific target decomposition, enrichment, PPI hub prioritization, docking, optional transcriptomic cross-checks, and conservative mechanistic synthesis. Covers five study patterns and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

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 complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk review.

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。

Identifies translationally meaningful paths for bioinformatics findings by mapping omics or computational discoveries to diagnosis, stratification, prognosis, treatment-response, monitoring, or target-nomination use cases, while auditing bridge evidence, assayability, and validation burden. Use this skill when a user wants to know whether a bioinformatics finding can be framed as a stronger translational topic without overclaiming clinical relevance. Always separate statistical signal from translational value, and never imply clinical utility, targetability, or validation depth without explicit evidence support.

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 analyzing transcription factor (TF) regulatory networks using Dorothea database. Input gene list, identify regulating transcription factors, generate TF-Target network visualization. For: transcription factor enrichment analysis, gene regulatory network research.

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。

Assesses whether a medical research topic is worth starting now by separating true novelty from pseudo-novelty, auditing real feasibility under stated resource constraints, and forcing a concrete start / narrow / redesign / stop decision. Always require explicit assumptions and never fabricate references, datasets, resource availability, precedent studies, or publication claims.

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。

Matches your study to appropriate journals based on topic, design, and evidence strength. Use when deciding where to submit a manuscript, comparing journal options by impact factor vs scope fit vs method tolerance, or finding a realistic submission target after a rejection. Also triggers on "where should I submit this paper", "which journal is best for my study", "find journals for my manuscript", "is this a good fit for [journal]", or "I need a journal with IF around X".

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。

Local drop-in API emulator for Vercel, GitHub, Google, Slack, Apple, Microsoft, AWS, Clerk, Linear, Twilio, and other developer APIs. Use when the user needs to start emulated services, configure seed data, write tests against local APIs, set up CI without network access, or work with the emulate CLI or programmatic API. Triggers include "start the emulator", "emulate services", "mock API locally", "create emulator config", "test against local API", "npx emulate", or any task requiring local service emulation.

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 skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or requests 3-5 year financial planning for a startup.

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 skill should be used when the user asks about "key startup metrics", "SaaS metrics", "CAC and LTV", "unit economics", "burn multiple", "rule of 40", "marketplace metrics", or requests guidance on tracking and optimizing business performance metrics.

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。

Für Redline Kommentar AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.

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。

Für Klauselinventar und Scope: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.

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。