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概要と使いどころ
Perform comprehensive cloud asset inventory and relationship mapping using Cartography to build a Neo4j security graph of infrastructure assets, IAM permissions, and attack paths across AWS, GCP, and Azure.
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。
Provides AI and machine learning techniques for CTF challenges. Use when attacking ML models, crafting adversarial examples, performing model extraction, prompt injection, membership inference, training data poisoning, fine-tuning manipulation, neural network analysis, LoRA adapt
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。
Personal App-in-Skill customer-support desk (help desk) that triages incoming support tickets from email, WhatsApp, web chat, contact forms, and WeChat, drafts KB-grounded replies, and proposes actions, then holds every send behind a human approval queue with a pre-send quality gate (support-qa) that outputs SHIP/FIX/BLOCK, plus SLA and CSAT tracking. Use when the user invokes $kelly-support or /kelly-support, mentions 客服 / 工单 / 支持台, a support desk, help desk, customer service, support tickets, ticket triage, a knowledge base or canned macros, SLA / first-response time, CSAT, escalations, or refund requests, wants incoming tickets triaged into a needs_review → approved → done pipeline, agent-drafted replies grounded in a knowledge base and reviewed before sending, refunds and commitments gated behind human approval, or breaching-SLA tickets surfaced. This is the OPERATOR desk (agent + human), distinct from a visitor-facing chat bubble.
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。
Product-launch command desk (Busabase App-in-Skill) built on the RAMP discipline — Research / Assemble / Mobilize / Prove. The agent assembles the launch checklist and drafts launch assets, channel submissions (Product Hunt / Hacker News / directories), press pitches, and the launch-day runbook; the human approves the launch-readiness gate and steers launch day in a review UI. Use when the user invokes $kelly-launch or /kelly-launch, or mentions launching / shipping a product, a launch checklist or runbook, launch readiness, RAMP, Product Hunt / Show HN / press-kit / launch-email drafting, or wants to review and approve launch assets and channel submissions before they go public. This is launch OPERATIONS — the checklist, assets, submissions, and runbook — not a launch video (for a promo video use product-launch-video).
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。
Busabase-backed App-in-Skill CRM operator for contacts, companies, deals, and agent-drafted follow-ups in a reviewable follow-up queue. Use when the user invokes $kelly-crm or /kelly-crm, mentions CRM, pipeline, contacts, companies, deals, follow-ups, relationship management, meeting-note capture, outreach drafts, next steps, or wants to review/approve agent-drafted follow-up messages before they are sent through other channels.
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。
Outbound email-marketing desk (Busabase App-in-Skill) for building segments, drafting campaigns, newsletters, and sequences, running pre-send deliverability and subject-line QA, and approving every send before it is scheduled. Structured around the SEND discipline — Setup, Engage, Nurture, Deliver — with an email-quality-auditor gate (EQS score + SHIP/FIX/BLOCK verdict). Use when the user invokes $kelly-campaigns or /kelly-campaigns, or mentions email marketing, campaigns, newsletters, drip/welcome/win-back sequences, broadcasts, segments, subject-line A/B tests, deliverability (SPF/DKIM/DMARC/spam score/inbox placement), or wants to review and approve marketing email before it is sent. This is OUTBOUND marketing to a subscriber list, distinct from kelly-email inbox triage (incoming mail). 出站邮件营销：策划分群、起草营销活动 / 新闻邮件 / 邮件序列，发送前做可送达性与主题行质检，人工审批后再排期发送。
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 asked to map, crosswalk, align, compare, or gap-analyze any two cybersecurity frameworks, control catalogs, or regulatory requirements using NIST IR 8477 Set-Theory Relationship Mapping (STRM). Triggers on terms like "map controls", "crosswalk", "framework alignment", "gap analysis", or producing a STRM CSV output file.
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。
Generates publish-ready LinkedIn posts for B2B SaaS marketing leaders writing from an operator point of view: real decisions, real trade-offs, real constraints, and defensible lessons. Use when turning an internal observation, framework, campaign decision, miss, or shipped artifact into a public LinkedIn post. Best for demand generation, ABM, marketing ops, product marketing, and SaaS GTM leaders building credibility through practical operating insight. Not intended for generic brand posts, company announcements, sales outreach, or long-form content.
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 multi-touch pipeline attribution models and generates stakeholder-ready narratives from campaign performance data. Use when analyzing channel contribution to pipeline, preparing monthly/quarterly revenue reports for leadership, diagnosing pipeline misses, modeling budget reallocation scenarios, or translating raw attribution data into board-deck language. Designed for B2B SaaS demand gen teams that report on pipeline and revenue, not leads or MQLs.
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。
Produces and audits externally published marketing copy where factual claims must survive scrutiny — landing pages, product pages, launch emails, one-pagers, search/social metadata. Every statistic, competitor comparison, capability description, and proof point is traced to a fetched source or the project's own documents, labeled, and adversarially verified before it ships. Use when writing or rewriting high-stakes marketing copy; when copy must pass legal, compliance, brand, or claims review; when the audience is skeptical technical or executive buyers; when the company has little or no customer proof yet (pre-launch, zero customers); or when auditing existing copy for unsupported claims, invented capabilities, unverified statistics, or AI-slop language.
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。
Detect abuse of legitimate Windows binaries (LOLBins) used for living off the land attacks. Monitors process creation, command-line arguments, and parent-child relationships to identify suspicious LOLBin execution patterns.
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 SOC performance metrics and KPI tracking dashboards measuring Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), alert quality ratios, analyst productivity, and detection coverage using SIEM data. Use when SOC leadership needs operational visibility, continuous improvement tracking, or executive-level reporting on security operations effectiveness.
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 real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.
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 meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership 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。
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
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。
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
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。
General mathematical methods skill for symbolic and numerical work; use when solving equations or deriving relationships.
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。
Follow-up scout for the Signals inbox itself. Watches reports that recently transitioned to resolved (an implementation PR merged) and, after a deployment soak window, re-measures the underlying problem to check the fix actually held — plus a strictly-gated escalation check on recently dismissed reports. Emits findings only when a shipped fix demonstrably didn't hold; confirmations and unverifiable verdicts become durable memory and an empty close-out. Self-contained peer in the signals-scout-* fleet — no dependencies on other 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。
Plan a user interview topic in PostHog — pick who to target (cohort, emails, or PostHog distinct IDs), draft what to ask about, and prepare the voice-agent context plus a question list. Use when the user asks to "talk to users", "check how users feel about X", "interview some customers", "set up a user interview", "run a user-research call", "find users to ask about Y", or otherwise wants qualitative feedback through a conversation. Walks the user through targeting (cohorts-list, persons-list, or accepting emails / distinct IDs directly), captures the topic, and prompts for agent context and questions before calling user-interview-topics-create. Cohort targeting is resolved to explicit emails/distinct_ids at create time — topics snapshot their audience and do not re-evaluate cohort membership later. Do NOT trigger when the user is uploading a recorded interview audio file (that's the separate UserInterview/transcript flow) or only browsing existing topics with user-interview-topics-list.
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。
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
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 database schemas — tables, relationships, indexes, constraints, and ORM setup. Covers relational design, normalization, and common patterns.
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 the analytics side of a PostHog experiment — exposure criteria (default `$feature_flag_called` vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio with `math` and `math_property`, retention with `retention_window_start` and `start_handling`), multivariate user handling ("Exclude" vs "First seen variant"), and how to read results once the experiment is live. Use when the user adds or edits a primary or secondary metric (e.g. "add a secondary metric tracking 'downloaded_file' per user"), sets up a ratio metric (e.g. "revenue from purchase_completed / pageviews"), sets up a retention metric (e.g. "$pageview → uploaded_file, 7-day window"), configures custom exposure (e.g. "only count users who hit /checkout"), changes multivariate handling, or asks "who is in the analysis?", "how do I measure impact?", "is this winning?", "what's the confidence level?", or "should I ship?".
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。
Author useful, low-noise log alerts on services in a PostHog project. Use when the user asks to set up alerts for their logs, suggest alerts they should add, or evaluate whether a service is worth monitoring. Covers service triage, baseline characterisation, threshold drafting, back-testing via simulate, and shipping with a notification destination.
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。
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
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。