2,050 件 ・ 関連度順
概要と使いどころ
Audit or improve manuscript statistical reporting, including experimental units, replication, uncertainty, tests, and figure statistics. Use for 统计审查、统计方法小节、图注统计 and reviewer concerns; compute new analyses only when requested with 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。
Provide evidence-grounded mock peer review of scientific manuscripts or excerpts, covering significance, validity, and major/minor concerns. Use for 模拟审稿、投稿前自审、审稿人视角评估; not author rebuttal drafting.
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。
Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.
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 before responding to pressure for agreement, manufactured urgency, authority appeals, or requests to certify unsupported claims; separate evidence from persuasion and state uncertainty.
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 periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access 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。
Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target's NT hash without a password reset. Use when BloodHound shows GenericWrite/GenericAll/AddKeyCredentialLink over a target, as a stealthier alternative to ForceChangePassword, during authorized red-team engagements.
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。
ISO/IEC 42001:2023 AI Management System (AIMS) specialist for compliance teams running internal audits. Three decisions: (1) Where are the gaps against Clauses 4-10 and what do we close first? (2) What goes in the AI risk register and which Annex A controls treat each risk? (3) What's the 12-month internal audit plan that satisfies Clause 9.2? Use when preparing for certification, scoping internal audit cycles, or onboarding AI systems into an existing ISMS (27001) / QMS (13485) program. NOT an executive AI strategy skill (see chief-ai-officer-advisor). NOT EU AI Act compliance (see compliance-team-eu-ai-act).
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。
Information Security Management System (ISMS) audit expert for ISO 27001 compliance verification, security control assessment, and certification support. Use when the user mentions ISO 27001, ISMS audit, Annex A controls, Statement of Applicability (SOA), gap analysis, nonconformity management, internal audit, surveillance audit, or security certification preparation. Helps review control implementation evidence, document audit findings, classify nonconformities, generate risk-based audit plans, map controls to Annex A requirements, prepare Stage 1 and Stage 2 audit documentation, and support corrective action workflows.
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。
/cs:compliance-readiness <program> — Multi-framework compliance officer 6-question forcing interrogation of any compliance program. Use before starting a new framework, planning the annual audit calendar, or preparing for certification stage 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。
Chief Customer Officer advisory for startups: retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy), customer segmentation strategy (differential investment across tiers + ICP fit scoring), CS team coverage model (pooled vs named CSM thresholds + ratio math), and CS team org evolution (CS vs Support vs AM distinctions). Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires. Strategic only — does not duplicate engineering/business-growth tactical skills.
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。
Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding whether to call an API or fine-tune, classifying AI use cases for regulatory risk, calculating when self-hosting pays off, sequencing AI hires, or when user mentions CAIO, AI strategy, model selection, foundation model, fine-tuning, EU AI Act, NIST AI RMF, AI governance, model risk, or AI economics. Strategic only — does not duplicate engineering AI/ML skills.
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。
Configures GKE edge networking, traffic routing, load balancing, and private service endpoints. Use when configuring Gateway API manifests, standard Ingress, Cloud Armor WAF security policies, Container-Native Load Balancing (NEGs), Private Service Connect (PSC), or Google-managed SSL certificates on GKE, and to troubleshoot Ingress and load-balancer 502/5xx errors, backend health-check failures, connection draining, and TLS/SSL policy enforcement. Don't use for core cluster IP planning, Dataplane V2 network policies, or node NAT egress (use gke-networking instead).
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。
Automate Dock Certs tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Digicert tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Certifier tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Bouncer tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Accredible Certificates tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Write minimal, reliable bug reproducers (repros) for any project. Use when: (1) a bug report or issue needs a test that reliably demonstrates the failure, (2) converting a described failure scenario into runnable code, (3) minimizing an existing complex test to its essential trigger conditions. Covers the full repro workflow: failure characterization, scope selection, writing the repro, verifying it fails for the right reason, and minimizing to the smallest possible trigger.
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。
Evaluate a skill against the Legal Skill Design Framework — thirteen design parameters (including trust-surface, freshness, schema validation, and conflict detection), three legal failure modes, and a three-band verdict (Ready / Some Concern / Material Concerns). Use when deciding whether to trust a community skill before installing it, before deploying a first-party skill to your team, or whenever the user asks "should I trust this?" or "is this skill well-designed?". Runs automatically as part of /legal-builder-hub:skill-installer.
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。
WPA/WPA2/WPA3-Enterprise (802.1X / EAP) attack methodology — EAP method identification (PEAP-MSCHAPv2, EAP-TTLS, EAP-TLS, EAP-GTC, EAP-PWD, EAP-FAST), evil-twin RADIUS attacks with eaphammer for credential capture, MSCHAPv2 challenge-response cracking, EAP-TLS client certificate theft paths (DPAPI, NDES, AD CS auto-enrollment), supplicant validation bypass (missing server cert validation, missing CN pinning, BYOD misconfigurations), and post-capture pivots into AD via cracked domain credentials. Use for corporate Wi-Fi engagements where the network is 802.1X authenticated.
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 statistically honest and uncertainty-aware visualizations. Use when the user needs help showing distributions, intervals, confidence, missingness, sampling effects, or analytical rigor in charts and dashboards.
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。
YouTube channel business email and contact extractor: accepts a channel id (UCxxx), handle (@name), or URL; navigates the channel About view; extracts the business email from the description text plus full channel metadata (name, id, country, subscriber count, view count, video count, joined date, external links classified as social/aggregator/personal). When the description has no email, follows non-social outbound links (personal site, business site, link aggregator) and scans those pages for an email so creators who place their inquiry email on their own site are still covered. Use when user mentions youtube channel email, youtube business email, youtube creator email, youtube contact email, youtube channel contact, youtube channel scraper email, youtube email finder, youtube influencer email, youtube outreach, youtube sponsorship contact, youtube partnership email, scrape email from youtube, get email from youtube channel, find youtube creator contact, extract youtube channel emails in bulk, youtube channel inquiry email, business inquiries youtube, brand deal email youtube, lead generation youtube creators, youtube creator outreach list, youtube channel about email, ytInitialData about, youtube channel id to email, youtube handle to email, youtube channel url to email, youtube about page scraper, channel about page email, youtube channel metadata, youtube channel social links, youtube channel external links, youtube channel description email, follow channel website for email, scrape creator personal website from youtube. Also applies to building creator/KOL contact databases for influencer marketing, agency lead lists, sponsorship prospecting, brand-creator collaboration sourcing, and enriching existing YouTube channel lists with contact info.
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。
Fetch Xiaohongshu (RedNote / xhs) user profile information and their published notes list by user ID, returning nickname, bio, follower/following counts, engagement totals, tags, and paginated notes with engagement stats. Use when user mentions user profile xiaohongshu, rednote creator profile, xhs influencer data, scrape xiaohongshu user, get blogger notes, xiaohongshu author info, KOL discovery xiaohongshu, rednote user stats, creator profile rednote, xiaohongshu blogger analysis, get xhs user followers, rednote influencer profile, xiaohongshu account info, xhs creator data, user notes list xiaohongshu, rednote account scrape, xiaohongshu KOL 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。
Opinionated Bayesian modeling workflow with PyMC and ArviZ. Contains critical guardrails (nutpie sampler, prior/posterior predictive checks, LOO-PIT calibration, prior sensitivity checks, 94% HDI, non-centered parameterizations, reproducible seeds) that agents won't apply unprompted — always consult before writing Bayesian model code. Trigger on: building probabilistic/Bayesian models, prior elicitation, MCMC inference, convergence diagnostics (divergences, R-hat, ESS), model comparison (LOO-CV, ELPD, stacking weights), hierarchical/multilevel models, count regressions, logistic regression with uncertainty, prior sensitivity analysis, reporting Bayesian results, or mentions of PyMC, ArviZ, InferenceData, credible intervals, posterior distributions, shrinkage, uncertainty quantification. Also trigger for model comparison, diagnosing sampling problems, choosing priors, or presenting stats to non-technical audiences.
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。