283 件 ・ 関連度順
概要と使いどころ
Determines when adrenal venous sampling may be skipped in primary aldosteronism. Applies to patients <35 years with spontaneous hypokalemia, marked aldosterone excess, and unilateral adrenal lesions suggestive of cortical adenoma on CT.
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。
Investigate and fix failing CI. Takes a PR reference, one or more CI run/job URLs, or freeform text describing where the failures are, then enumerates failing workflows/jobs/steps, determines the root cause (often one shared cause behind several red checks), proposes a fix plan, applies code changes, commits, pushes, watches the new runs, and repeats until checks pass. Use when the user says "fix CI", "CI is red", "checks are failing", "the build is broken on my PR", "fix the failing jobs", or pastes a failing CI run URL. Do NOT use for authoring new workflows, or for read-only diagnosis with no fix intent — use gha-log-reader for that.
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 opening edited files in the user's IDE. Reads settings from .agent-settings.yml to determine IDE and whether auto-open is enabled.
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。
Mid-run failure recovery for disease-market-sizing-orchestration. Inspects .cache/<slug>/ to determine which phase last completed and which phase to run next. Use when orchestration was interrupted and user wants to continue without restarting from phase 1.
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。
Upgrade or synchronize Agent Skills, or determine a Skill's source and ownership across runtimes and roots. Use only for those lifecycle decisions. Do not use for installation, creation or editing, validation, inventory, usage statistics, general audits, cleanup, packaging, publishing, or ordinary file and package 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。
AI crawler access analysis. Checks robots.txt, meta tags, and HTTP headers to determine which AI crawlers can access the site. Provides a complete access map and recommendations for maximizing AI visibility while maintaining appropriate control.
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 citability scoring and optimization. Analyzes web page content to determine how likely AI systems (ChatGPT, Claude, Perplexity, Gemini) are to cite or quote passages from the page. Provides a citability score (0-100) with specific rewrite suggestions.
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。
Resolve, validate, and audit manuscript integrity and applicable requirements for academic manuscripts and paper artifacts. Use when Codex needs to determine active paper rules from manuscript state, paper type, venue, submission stage, or workflow mode; lint a LaTeX paper project; assess submission readiness; create or update a paper policy profile; explain why a rule is active; or validate the paper-policy registries. Do not use as the primary skill for prose drafting, peer review, rebuttal writing, citation discovery, or figure/table creation.
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。
Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.
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。
Determine the best Anthropic architecture for your project by analyzing requirements and recommending the optimal combination of Skills, Agents, Prompts, and SDK primitives.
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。
Conduct a defensible cybersecurity risk assessment using the NIST SP 800-30 Rev 1 methodology: prepare scope and a risk model, identify threat sources and threat events, identify vulnerabilities and predisposing conditions, determine likelihood and impact, compute risk, and communicate results as a prioritized risk register. Use when an organization needs an actual risk *assessment* (not a maturity score), when a control framework (CSF, ISO 27001, RMF, SOC 2, PCI) requires a documented risk analysis as input, when leadership asks "what are our top risks and how bad are they", when assessing risk for a new system or major change, or when building a risk register from scratch. This is the methodology that feeds framework selection, ATO packages, and treatment decisions. Keywords: risk assessment, NIST 800-30, threat modeling, likelihood and impact, risk register, risk analysis, threat sources, vulnerabilities, risk determination, qualitative risk, risk matrix, residual risk, risk treatment.
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。
Parse Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic investigation.
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 malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious document analysis, PDF exploit investigation, or suspicious attachment triage.
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 indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.
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。
Campaign attribution analysis involves systematically evaluating evidence to determine which threat actor or group is responsible for a cyber operation. This skill covers collecting and weighting attr
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。
Determine whether an app is ready to submit, then drive the current App Store release flow with asc, including validation, staging, review submission, first-time availability, subscriptions, IAP, Game Center, and App Privacy checks.
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。
Dieser Skill sollte genutzt werden, wenn der User private oder halbformale E-Mails schreiben, beantworten, absagen, nachfassen, kürzen, umformulieren oder im eigenen Stil entwerfen lassen will, besonders bei Terminen, offiziellen Absagen, freundlichen Kurzantworten und kontaktabhängigem Ton. Profilanalyse erst bei einem konkreten Mail-Schreibauftrag starten.
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。
Calendar skill with user-adaptive backend selection (Flag 3). Default: local SQLite store. Optional: Google Calendar MCP, Routinika or UpToday as backend — controlled via assist/prefs.json. Without preference the LLM asks the user interactively.
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。
Reads a project or processing description and returns a DRAFT data protection impact assessment pack: processing description, necessity and proportionality questions, a risk table with blank rating cells, mitigations to consider and open questions. Never rates risk, determines the lawful basis or judges adequacy; the DPO assesses and signs. Works from descriptions, never personal data. Use when the user asks to "start a DPIA for the new monitoring tool", "draft a data protection impact assessment", "scaffold a DPIA from this processing description" or "what would the DPO need for a DPIA on this". Do not use for redacting or de-identifying a document, use document-deidentification-pass instead; do not use for working out what data an incident exposed, use data-incident-impact-brief instead. Drafts for human review; never approves, authorises or signs off.
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, grade, rewrite, and issue funny evidence-backed tickets for generic AI-slop patterns in prose, social posts, UI/design, and code. Use when asked to de-slop writing, humanize AI copy, grade a draft, review a landing page or generated interface, remove vague claims and repetitive rhetoric, inspect AI-written code for generic abstractions and happy-path-only logic, or ticket someone for a specific quality offense. Do not use to determine whether AI authored something.
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。
Explain how a subsystem works, trace a runtime flow, or determine where code and ownership belong before making a change.
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。
Generative UI (GenUI) for Flutter using AI models like Google Gemini, Anthropic Claude, or OpenAI via the genui package. Use this skill when building dynamic AI-driven interfaces, conversational UI flows, server-rendered screen layouts, LLM-powered dashboards, chat-based UI generation, or implementing prompt-to-UI systems. Supports AI-generated widgets, reactive data binding, ContentGenerator integration, and A2uiMessageProcessor for real-time UI updates from AI responses. Ideal for apps where UI structure is determined by AI/LLM output rather than hardcoded layouts.
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 independent contractor payments, collect W-9s, determine 1099-NEC filing requirements, and avoid penalties. Covers the $600 threshold (2025) and $2,000 threshold (2026), Jan 31 deadline, corporate exceptions, backup withholding, and penalty schedule ($60–$660/form). Trigger on "1099", "contractor payment", "do I need to file a 1099", "W-9", "independent contractor".
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。
Determine whether to expense or depreciate business assets using the de minimis safe harbor ($2,500), Section 179 ($1,220,000 limit), bonus depreciation (phase-out 2024–2027), or MACRS schedules. Track asset basis, useful life, and accumulated depreciation. Trigger on "depreciate", "Section 179", "bonus depreciation", "capitalize or expense", "asset tracking", "de minimis".
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。