3,493 件 ・ 関連度順
概要と使いどころ
Convert PRDs to prd.json format for the Ralph autonomous agent system. Use when you have an existing PRD and need to convert it to Ralph's JSON format. Triggers on: convert this prd, turn this into ralph format, create prd.json from this, ralph json.
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-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
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。
15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.
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。
Interact with DeerFlow AI agent platform via its HTTP API. Use this skill when the user wants to send messages or questions to DeerFlow for research/analysis, start a DeerFlow conversation thread, check DeerFlow status or health, list available models/skills/agents in DeerFlow, manage DeerFlow memory, upload files to DeerFlow threads, or delegate complex research tasks to DeerFlow. Also use when the user mentions deerflow, deer flow, or wants to run a deep research task that DeerFlow can handle.
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 Product Requirements Document (PRD) for a new feature. Use when planning a feature, starting a new project, or when asked to create a PRD. Triggers on: create a prd, write prd for, plan this feature, requirements for, spec out.
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。
生成用于构建和发布 .NET 6 MAUI iOS 项目的 Azure Pipelines YAML 配置，包含 DotNetCoreCLI 任务配置、RuntimeIdentifier 设置及 IPA 文件重命名功能。
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。
Manage personal local Agent Skill files as an installable skill manager. Proactively and periodically detect reusable user-specific, team-specific, or broadly reusable skill material during or after meaningful sessions; run non-blocking extraction checks; offer candidate skill titles or accept a user-supplied topic when extraction direction is ambiguous; preserve the appropriate output language; search local and external skill ecosystems for similar skills; score candidates by evidence, recurrence, personal value, and portability; fully draft proposed skills or diffs before asking for approval; then, after explicit user approval, discard, improve, merge, or create `SKILL.md` folders.
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。
World-class autonomous sales and revenue skill system. Use ANY time the user asks to sell, pitch, prospect, close, negotiate, launch, monetize, build funnels, write outreach, craft proposals, develop pricing, design offers, write sales copy, create email sequences, plan campaigns, position products, handle objections, create playbooks, build pipeline, forecast revenue, develop GTM strategy, optimize conversions, write ad copy, create sales decks, score leads, nurture prospects, upsell, cross-sell, retain customers, write case studies, price products, structure enterprise deals, create battle cards, script discovery calls, build affiliate programs, plan product launches, create webinar funnels, design pricing pages, A/B test offers, analyze unit economics, calculate LTV/CAC, or ANY other sales, revenue, monetization, go-to-market, or commercial growth task. If it involves selling, revenue, deals, pipeline, or commercial strategy — USE THIS SKILL. Trigger aggressively.
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。
Quarterly Silicon Agent performance evaluation with ByteDance-style calibration, forced distribution ranking, dual-track (technical/management) assessment, and automated score calculation. Includes real evaluation forms, calibration meeting scripts, and PIP templates.
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。
Turn one ecommerce content core into channel-ready publish packs (X, WeChat, Xiaohongshu, TikTok notes) with platform-specific formatting and CTA adaptation.
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。
Qualify an inbound lead — "is this lead worth my time", "qualify this lead", "should I take this client". Applies MEDDIC and SPIN scoring and returns a verdict with reasoning.
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。
Diagnose why a social post performed — "analyze this post", "why did this post flop", "why did this post do well", "what should I change". Scores hook strength, clarity, tension and call to 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。
Triage requirements, specs, or tickets. Detect input (pasted text, markdown path, tracker ticket id/URL, or empty prompt). Explore codebase + docs, score completeness, ask clarifying questions, write a markdown report. Trigger when user says "triage", "review this spec", "is this requirement complete", or provides a ticket/spec to assess.
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。
Manage the Matrix/Virgo-Core Proxmox VE cluster (nodes Foxtrot, Golf, Hotel - MINISFORUM MS-A2 with AMD Ryzen 9 9955HX). Covers VM provisioning, VLAN networking, CEPH storage, and automation via Python (proxmoxer), Ansible (community.general.proxmox), and Terraform (Telmate/proxmox).
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。
Guide for using the Microsoft Fluent UI Blazor component library (Microsoft.FluentUI.AspNetCore.Components NuGet package) in Blazor applications. Use this when the user is building a Blazor app with Fluent UI components, setting up the library, using FluentUI components like FluentButton, FluentDataGrid, FluentDialog, FluentToast, FluentNavMenu, FluentTextField, FluentSelect, FluentAutocomplete, FluentDesignTheme, or any component prefixed with "Fluent". Also use when troubleshooting missing providers, JS interop issues, or theming.
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。
INVOKE THIS SKILL for LLM-as-judge evaluation workflows on Arize: creating/updating evaluators, running evaluations on spans or experiments, tasks, trigger-run, column mapping, and continuous monitoring. Use when the user says: create an evaluator, LLM judge, hallucination/faithfulness/correctness/relevance, run eval, score my spans or experiment, ax tasks, trigger-run, trigger eval, column mapping, continuous monitoring, query filter for evals, evaluator version, or improve an evaluator prompt.
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。
Core principles and golden rules for writing production-quality Ansible automation, covering FQCN requirements, module selection guidance, and execution patterns using uv run.
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。
Self-healing stability monitor for AI agents - 5 core checks + 15 extended checks, auto-recovery, health scoring
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。
Retrieve Aavegotchi NFT data by gotchi ID or name on Base. Returns traits, wearables, rarity scores, kinship, XP, level, and owner data.
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。
Human verification for AI agents. Submit claims, draft responses, or observation requests to human domain experts via the 2O API. Returns structured verdicts with confidence scores and evidence.
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。
Give Hermes phone capabilities without core tool changes. Provision and persist a Twilio number, send and receive SMS/MMS, make direct calls, and place AI-driven outbound calls through Bland.ai or Vapi.
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 technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants measurable accessibility, performance, responsive, theming, or anti-pattern findings—not when they mainly want an overall UX critique or final visual/detail polish.
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。
Analyzes provided content for quality, E-E-A-T signals, and SEO best practices. Scores content and provides improvement recommendations based on established guidelines. Use PROACTIVELY for content 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。
Expert performance engineer specializing in modern observability, application optimization, and scalable system performance. Masters OpenTelemetry, distributed tracing, load testing, multi-tier caching, Core Web Vitals, and performance monitoring. Handles end-to-end optimization, real user monitoring, and scalability patterns. Use PROACTIVELY for performance optimization, observability, or scalability challenges.
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。