3,526 件 ・ 関連度順
概要と使いどころ
Adecuar un proyecto Python YA EXISTENTE (legacy o con motor viejo embebido) al motor portable, orquestando las skills y scripts existentes en el orden correcto. Usar cuando se incorpora un repo con codigo previo como repo_destino. No usar para un destino nuevo o limpio (ver setup-agent-system) ni para crear un proyecto desde cero (ver scaffold-python-project).
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。
Systematic debugging playbook for the Forge agentic loop (src/core/loop.ts and src/agents/executor.ts). Use when a task is stuck, looping, or producing wrong tool calls.
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。
Systematic debugging playbook for the Forge agentic loop (src/core/loop.ts and src/agents/executor.ts). Use when a task is stuck, looping, or emitting wrong tool calls.
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。
Lead Qualification And Scoring Specialist. Use to define ICP filters, score inbound and outbound leads, and improve pipeline focus for a founder-led sales motion.
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 and audit PFC2D/PFC3D 5.0 model foundations for asphalt cases, including lifecycle, domain, balls, walls, clumps, groups, ranges, top-level cmat, staged saves, and source-version purity.
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。
命理圆桌会——多流派命理师（盲派、子平格局派、调候派、民国新派）对同一八字命盘进行圆桌论命：多视角总评、交叉质疑、可证伪断语、逐轮记分复盘。用户提到八字、四柱、命盘分析、批命、论流年大运、盲派/格局/调候论命、"多个命理师讨论"、验证式论命时使用本 skill；即使用户只是贴出一张八字排盘求分析，也应启用（可用轻量模式）。Multi-school Chinese BaZi (Four Pillars) roundtable reading: several fortune-tellers from rival schools analyze the same natal chart, cross-examine each other, issue falsifiable predictions, and keep score. Use whenever the user asks about BaZi, Four Pillars, Chinese astrology chart reading, or destiny 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。
"Interpret the three core financial statements (income statement, balance sheet, cash flow statement) to assess business health and performance. Use this skill when the user needs to read financial statements, understand profitability vs cash flow, evaluate a company's financial position, or prepare for investor/board meetings — even if they say 'explain these financials', 'are we making money', 'read this annual report', or 'what do these numbers mean'.".
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。
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
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。
"Implement VADER sentiment analysis for social media text scoring. Use this skill when the user needs to analyze sentiment in tweets, reviews, or social posts, compute compound sentiment scores, or classify text polarity — even if they say 'is this positive or negative', 'sentiment of these comments', or 'social media mood 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。
"Corporate innovation-governance toolkit integrating Stage-Gate process, 3 Horizons model, innovation portfolio management, open innovation, corporate venture capital (CVC), innovation KPIs, and intrapreneurship. Use for innovation-portfolio design, second-curve planning, innovation-project review gating, open-innovation evaluation, CVC setup, innovation-KPI design, or managing tension between core and new businesses. Triggers: 『第二曲線』『創新專案怎麼管』『新事業孵化』『收購投資新創』『Stage-Gate』『研發投資組合』『內部創業』『開放式創新』『CVC』『3 Horizons』『創新 KPI』. For Taiwan EMBA innovation-management/strategy/technology-management cases (台大／中山). Startup basics: use Asgard `ux-lean-startup`; innovation theory: use Asgard `grad-disruptive-innovation`, `grad-ambidexterity`; 家族二代接班治理: use `biz-corporate-governance` 或 `ops-talent-strategy`; ESG/淨零策略結合: use `biz-net-zero-transition`.".
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。
"Apply the Balanced Scorecard (BSC) framework to translate strategy into measurable objectives across Financial, Customer, Internal Process, and Learning & Growth perspectives. Use this skill when the user needs to set strategic KPIs, create a strategy map, align organizational goals, or connect daily operations to strategic vision — even if they say 'how do we measure strategy execution' or 'our KPIs feel disconnected'.".
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 credit scoring models to predict default probability from borrower characteristics. Use this skill when the user needs to assess creditworthiness, build a credit scorecard, or evaluate lending risk — even if they say 'predict default risk', 'credit scoring', or 'loan approval model'.".
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。
"Calculate Wilson Score confidence intervals for ranking items by positive proportion with sample size correction. Use this skill when the user needs to rank products by ratings, sort content by approval rate, or build a 'best rated' list that accounts for sample size — even if they say 'rank by star rating', 'best rated with few reviews', or 'confidence-adjusted rating'.".
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。
Builds and audits a concept-ontology for a regelrecht corpus to decide and verify reference types — cross-law source-binding vs intra-law source-binding vs open-norm leaf vs external-fact leaf — and to catch concept conflation across laws. Core principle: a value's reference type is fixed by WHO derives it, and a binding is sound only when producer and consumer denote the SAME concept; the lexical surface (the word in the text) is not the concept. Detects false friends (one term, different concepts — e.g. a register-based vs a factual "naar de omstandigheden"-based residence/ingezetene concept), orphan plain-params (a value a regulation actually derives, modeled as a brute input), negation/complement re-entry (¬X modeled as an independent leaf next to X), and duplication (one concept re-entered as several independent leafs, losing the single-source-of-truth invariant). Produces a law-level glossary and a stelsel-level concept map with sound same-concept binding edges and flagged lexical-match-but-concept-mismatch edges. Use when deciding whether a value should be cross-law/intra-law/leaf, when the same term means different things across laws, or when a binding might silently conflate concepts.
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。
Universal prose writing and audit skill. Apply for writing, editing, or reviewing prose, and for explicit requests to score text or flag formulaic AI-writing patterns. Do not activate for ordinary factual, code, or configuration tasks.
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。
Facilitate SAFe 6.0 PI Planning events. Structure the 2-day cadence, generate PI Objectives with Business Value scores, build the Program Board for dependency visualization, and run the Confidence Vote. Use before every Program Increment when the organization follows SAFe.
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 KPI dashboards with SMART metrics, visualization selection, alert thresholds, and refresh cadence. Covers leading vs lagging indicators, data dictionary, and stakeholder-specific views. Use when building operational dashboards, executive scorecards, or team performance views.
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。
Assess organizational readiness for financial audits (internal or external). Map assertions to account balances, check evidence completeness, score readiness using a Red/Amber/Green framework, and generate a remediation timeline. Aligned with SOX, IFRS, and GAAP audit standards. Use before scheduled audits or when preparing for first-time compliance.
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。
Audit data quality across six DAMA DMBOK dimensions — Completeness, Accuracy, Consistency, Timeliness, Validity, Uniqueness. Produces a scored data quality report with issue log and remediation plan. Use when profiling datasets, onboarding new data sources, or building data quality gates.
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 OSINT reconnaissance using the MITRE ATT&CK Reconnaissance framework. Email harvesting with SMTP verification, subdomain takeover detection, certificate transparency mining, Shodan/Censys intelligence, Wayback Machine historical analysis, social media profiling, cloud storage enumeration, document metadata extraction, DNS history, credential leak checks, and passive infrastructure mapping. Uses theHarvester, amass, dnsrecon, fierce, dnstwist, dmitry, whatweb, wafw00f, exiftool, metagoofil, smtp-user-enum, swaks, waybackurls, subfinder, and crt.sh. Pure reconnaissance — no active exploitation. Produces: confidence-scored findings, infrastructure diagram, employee roster, email pattern confirmation, subdomain takeover candidates. Chains into /pentester for active testing.
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。
Detects sensitive data stored insecurely on mobile devices (Android/iOS). Trigger on: SharedPreferences, NSUserDefaults, SQLite, Room DB, DataStore, Core Data, Keychain misconfiguration, external storage, backup exposure, plaintext files, unencrypted databases, adb backup, iCloud backup, NSFileProtection, EncryptedSharedPreferences, SQLCipher, allowBackup, FLAG_SECURE, keyboard cache, sensitive logs. Covers MASVS-STORAGE-1 (local storage) and MASVS-STORAGE-2 (exposure to unauthorized actors).
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 and exploit Prototype Pollution vulnerabilities in JavaScript applications to achieve client-side Cross-Site Scripting (XSS), bypass authentication, or execute Remote Code Execution (RCE) on Node.js servers by manipulating the core Object prototype.
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 and exploit flaws in the core business rules and logic of web applications. This skill focuses on manipulation of application workflows, pricing, inventory limitations, and multi-step processes. Use this skill when bug hunting or testing e-commerce, banking, or SaaS platforms where standard technical vulnerabilities (e.g., XSS/SQLi) are not present but the application's logic is flawed.
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。
Systematically extract hidden system prompts, core directives, and invisible context intentionally concealed within Large Language Model (LLM) applications. This skill utilizes targeted linguistic engineering and boundary manipulation to bypass prompt opacity.
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。