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概要と使いどころ
"Apply Theory of Constraints (TOC) to identify and manage system bottlenecks. Use this skill when the user needs to find what limits throughput, optimize a constrained process, apply the Five Focusing Steps, or implement Drum-Buffer-Rope scheduling — even if they say 'our output is stuck', 'what's the bottleneck', or 'why can't we produce more'.".
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。
Extract sensitive training data and internal capabilities from AI models through repeated programmatic querying. Use this skill when testing LLMs and ML models for data privacy leaks, intellectual property exposure, or unintended memorization. Covers membership inference, prompt extraction, training data reconstruction, and API boundary 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。
Extract sensitive training data (PII, API keys, intellectual property, or code) directly from a deployed Large Language Model (LLM). This AI Red Teaming skill focuses on forcing models to regurgitate memorized, unredacted data from their massive internet-scraped datasets through repetition attacks, prefix continuation, and context window manipulation.
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。
Active Directory and network lateral movement assessment. Pass-the-hash, pass-the-ticket, Kerberoasting, AS-REP roasting, NTLM relay, SMB relay, WMI/WinRM/PSRemoting abuse, constrained/unconstrained delegation, RBCD, cross-trust exploitation, and pivoting. Uses impacket, netexec, enum4linux-ng, smbmap, smbclient, bloodhound-python, Responder, ntlmrelayx, mitm6, and ldap-utils. Chains from /post-exploit or /credential-audit.
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。
Active Directory security audit using the MITRE ATT&CK framework. Full domain enumeration, trust mapping, GPO analysis, ACL abuse paths, ADCS attacks (ESC1-ESC8), delegation abuse (constrained/unconstrained/RBCD), fine-grained password policies, LAPS deployment, service account security, and Kerberos configuration. Uses enum4linux-ng, netexec, impacket, ldapsearch, certipy-ad, bloodhound-python, and rpcclient. Produces attack path diagrams, prioritized risk register, and PoCs. Chains into /gh-export for issue filing.
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 a prompt the user is about to send to Claude (or another coding AI) for completeness and effectiveness. Use this skill whenever the user shares a prompt and asks for feedback — phrases like "is this prompt good", "audit my prompt", "review this prompt", "will Claude understand this", "improve this prompt", "is this enough context". Also trigger proactively when you notice the user is about to dispatch a vague, under-specified, or over-constrained prompt for non-trivial work. Checks the 6 essential elements (goal, scope, existing patterns, constraints, verification, done definition), flags what's missing, explains why each gap matters, and produces an improved rewrite. Treat this skill as the litmus test for "Be Claude's PM" — if the prompt fails the audit, the work that follows will probably fail too.
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。
Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire or the AI annex buyers now attach to it, executing sales sequences, coaching qualification, or deciding what the website's AI chat agent is allowed to say. Also triggers on: outbound, cold outreach, reply handling, reply classification, out-of-office replies, auto-replies counted as replies, our reply rate is inflated, prospect replied remove me, opt-out by reply, is this list ready to send, launch readiness, CRM segment outbound, we emailed a current customer, outbound hit an open opportunity, ownerless leads, prospects engaging our competitors, competitor connections, displacement list, is this personalization creepy, can we mention they visited our site, signal freshness, deal strategy, pipeline, battle card, objection handling, common objections, why do we keep hearing this objection, mine call transcripts for objections, objection register, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, AI security questionnaire, AI annex, AI vendor due diligence, the buyer is asking if we train on their data, do you train on customer data, which model do you use, model provider sub-processor, AI subprocessor disclosure, where does inference run, can the customer turn the AI feature off, AI-CAIQ, CSA AI Controls Matrix, ISO 42001, ISO/IEC 42001, NIST AI RMF, EU AI Act Article 50, are we a provider or a deployer, AI feature disclosure, our model vendor changed and nobody told the buyer, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss, website chatbot, chat widget, AI chat agent, AI SDR, inbound AI SDR, conversational marketing, live chat, what should our chatbot be allowed to say, our chatbot quoted the wrong price, the bot promised a discount, do we have to disclose it is AI, EU AI Act chatbot disclosure, chatbot handoff to sales, chat transcript review, prompt injection on our chatbot, Drift, Qualified, Intercom.
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 a task needs the judgment of a certified athletic trainer — triaging an on-field or on-court injury, deciding same-day return-to-play vs. refer-out, running a concussion sideline assessment and graduated return-to-sport progression, recognizing exertional heat stroke or another sudden-death emergency, or writing the objective findings that justify a clearance decision.
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。
Language-specific guidelines for producing high-quality Traditional Chinese (zh-TW) content: script, full-width punctuation, spacing, forms of address, grammar constraints, and Taiwan terminology. Includes the no-calque rule against literal translations of English phrasal verbs such as 折入 for fold in. Use when writing any kind of Chinese content. Including blog posts, notes, technical articles, technical writing, chitchat, social media posts, etc., even when you are just sending a text message. Also use when reviewing or editing existing Chinese content for language and terminology compliance. Always apply `writing-style-guideline` alongside this skill for structure, tone, rhetorical constraints, and banned phrases.
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。
Analyze learning management and training pathway systems for prerequisite mapping, competency-based progression, adaptive sequencing, and credential stacking.
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 manufacturing production optimization systems for OEE (Overall Equipment Effectiveness) calculation accuracy, Six Big Losses categorization, job shop and flow shop scheduling algorithms (LP, MIP, constraint programming, genetic algorithm), Theory of Constraints bottleneck detection.
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 manufacturing predictive maintenance systems for OPC-UA/MQTT sensor data pipelines, time-series storage retention, ML model lifecycle (training-serving skew, drift detection, retraining triggers), MTBF/MTTF/MTTR reliability calculations, Weibull survival 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。
Implement and debug OAuth 2.0 DPoP (RFC 9449) refresh token sender-constraining for WebCrypto, Node.js ES6, and browser runtimes integrating with Google's OAuth platform. Use when configuring non-extractable asymmetric key pairs (P-256), generating DPoP Proof JWTs for authorization code exchange and token refresh, or handling 400 use_dpop_nonce challenge retry loops at oauth2.googleapis.com/token. Don't use for unconstrained OAuth 2.0 flows (where refresh tokens are not bound to a client key pair), or for Google Cloud IAM / service account authentication.
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 this skill when building, reviewing, or refreshing a RACI (Responsible / Accountable / Consulted / Informed) matrix for a Salesforce project so that every Salesforce-specific decision — data model change, automation tier choice, security model, integration boundary, deployment, license/edition — has exactly one accountable owner and a documented escalation path that downstream agents can route to. Trigger keywords: RACI matrix salesforce project, stakeholder authority salesforce, escalation path salesforce decisions, who approves data model change, salesforce decision rights, REFUSAL_NEEDS_HUMAN_REVIEW routing. NOT for the change advisory board operating model itself (use admin/change-management-and-deployment). NOT for end-user training rollout plans (use admin/change-management-and-training). NOT for the technical mechanics of permission set assignment authority (use admin/permission-set-architecture). NOT for pure stakeholder requirements elicitation (use admin/requirements-gathering-for-sf). More trigger keywords: who approves a sandbox refresh, who signs off a data load, release update activation owner, delegated admin authority vs RACI, multi-org decision rights, escalation time-box.
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 this skill when prioritizing a Salesforce backlog with the MoSCoW method (Must / Should / Could / Won't) plus an effort + value lens, deciding what fits in the next sprint or release, and using WSJF as a tie-break when MoSCoW alone produces ties. Trigger keywords: MoSCoW prioritization, must should could won't, WSJF salesforce, prioritize salesforce stories, sprint commit, backlog grooming. NOT for story writing or splitting (use admin/user-story-writing-for-salesforce). NOT for release train planning (use agents/release-train-planner). NOT for sizing/estimation method debates — this skill assumes a sizing convention is already in place.
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。
Configuring Salesforce In-App Guidance: floating, docked, and targeted prompts, multi-step walkthroughs, audience targeting, scheduling, and adoption analytics. Use when designing user onboarding or feature adoption programs in Lightning Experience. Covers the Prompt metadata type, promptVersions, displayType, uiFormulaRule, stepNumber, isPublished, PromptAction and PromptError. NOT for guidance on a record's Path — use admin/path-and-guidance. NOT for adoption and training — use admin/change-management-and-training.
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 this skill when setting up or modifying product bundles, product options, product rules, configuration attributes, and product features in Salesforce CPQ. Trigger keywords: CPQ product bundle, product rule, option constraint, feature configuration, dynamic bundle, filter rule, configuration attribute, bundle nesting. NOT for plain Products and Pricebooks without CPQ — use admin/products-and-pricebooks. NOT for moving an existing CPQ catalog between orgs — use data/product-catalog-migration-cpq. NOT for price rules, price actions or discount schedules — use admin/cpq-pricing-rules.
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 this skill when driving adoption of CRM Analytics (Einstein Analytics) across an org — the Analytics Adoption App for measuring who uses which dashboards, embedding analytics into Lightning pages, pinning dashboards to the Analytics home page, self-service personas, and analytics success metrics. Triggers: analytics adoption, dashboard usage tracking, embedded analytics strategy, self-service analytics enablement, CRM Analytics rollout. NOT for building the dashboards — use admin/analytics-dashboard-design. NOT for the app, datasets and lenses — use admin/crm-analytics-app-creation. NOT for non-analytics rollout training — use admin/change-management-and-training.
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。
PXE/netboot 経由で Debian + HW RAID10 を自動インストール (OpenWrt ローカル TFTP + embed ipxe.efi + IPv4 リテラル mirror)。BMC USB redirector が累積劣化した機種 (TX1320 M3 等) や、 cross-site 拠点の install に使う。phase 19 で training-tx1320 で完遂、 物理操作なしで自力 SSH まで到達。
Fujitsu iRMC S4 (TX1320 M3 等) の電源・BIOS・RAID 操作 + BIOS 設定リファレンス。Redfish (HTTPS + SECLEVEL=0) 経由の電源/ブート操作 + iRMC Web UI/KVM 経由の手動 BIOS/RAID 操作手順 + 全 BIOS 設定項目の網羅リファレンス (bios/)。training-tx1320 対応。
Maintain SESSION-STATE.md, the durable within-session memory that survives context compaction. Use when a constraint, settled decision, existing-infrastructure (survey) finding, or open thread must persist across a long session so it is not re-derived or re-litigated. Triggers on /state, "remember this for the session", "record this constraint/decision", or after surveying what already exists. For cross-session/personal memory use .claude/memory/ on Claude or native memories on Codex; for repo-derivable facts, do not record at all.
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。
Query China Railway 12306 for train schedules, remaining tickets, and station info. Use when user asks about train/高铁/火车 tickets, schedules, or availability within China.
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 a refined Scandinavian visual system with a neutral black-and-white foundation, restrained sans-serif typography, purposeful product imagery, generous spacing, clear page chapters, and minimal decoration. Use when the user invokes /scandinavian-design or requests a Nordic, monochrome, calm, spacious, restrained, or minimalist interface.
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 compliance analysis for EU AI Act, ISO 42001, NIST AI RMF, GDPR, OECD, financial services regulations (SEC, FCA, FINRA, DORA, MiFID II), and other frameworks. Use when asked to generate a compliance checklist for an AI tool or use case, determine if a risk assessment is required, score an AI tool's risk level, identify where an AI tool or use case could run afoul of regulatory requirements, perform a gap analysis, recommend remediation steps, assess a vendor, draft an acceptable use policy, map training requirements, or review jurisdiction-specific AI rules. Triggers on phrases like "compliance checklist", "risk assessment", "risk score", "does this comply", "EU AI Act", "ISO 42001", "NIST AI RMF", "AI governance", "gap analysis", "vendor assessment", "acceptable use policy", "MNPI", "AI training requirements", or any request to evaluate an AI tool or use case for regulatory compliance or risk.
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。