Detect Layer 2 ARP poisoning/spoofing by deploying ARPWatch, Dynamic ARP Inspection (DAI), Wireshark packet analysis, and custom Python monitoring scripts that flag gratuitous ARP floods, IP-to-MAC mapping changes, and duplicate IP addresses. Use when investigating suspected man-in-the-middle interception or session hijacking on a local network segment, or when building layer-2 anomaly detection for a SOC.
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。
mukul975/Anthropic-Cybersecurity-Skills☆ 3.4万2026年8月31日 更新
Conducts authorized wireless network penetration tests to assess the security of WiFi infrastructure by testing for weak encryption protocols, captive portal bypasses, evil twin attacks, WPA2/WPA3 handshake capture, rogue access point detection, and client-side attacks. The tester evaluates wireless authentication, network segmentation, and the effectiveness of wireless intrusion detection systems. Activates for requests involving wireless pentest, WiFi security assessment, WPA2/WPA3 testing, or rogue access point 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。
mukul975/Anthropic-Cybersecurity-Skills☆ 3.4万2026年8月31日 更新
Executes containment strategies to stop active adversary operations and prevent lateral movement during a confirmed security breach. Implements short-term and long-term containment using network segmentation, endpoint isolation, credential revocation, and access control modifications. Activates for requests involving breach containment, lateral movement prevention, network isolation, active threat containment, or live incident response.
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。
mukul975/Anthropic-Cybersecurity-Skills☆ 3.4万2026年8月31日 更新
Implement Microsoft's Enhanced Security Admin Environment (ESAE) tiered administration model for Active Directory, covering Tier 0/1/2 separation, privileged access workstations (PAWs), administrative forest design, and authentication policy silos. Use when designing or hardening AD privileged-access architecture, segmenting Domain/Enterprise Admin accounts into tiers, or containing lateral movement and credential theft (pass-the-hash, Kerberoasting, golden tickets).
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。
mukul975/Anthropic-Cybersecurity-Skills☆ 3.4万2026年8月31日 更新
Configures Zscaler Private Access (ZPA) to replace traditional VPN with zero trust network access by deploying App Connectors, defining application segments, configuring identity- and device-posture-based access policies, and integrating with IdPs. Use when replacing VPN concentrators with ZTNA or providing remote users secure access to internal applications without network-level connectivity.
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。
mukul975/Anthropic-Cybersecurity-Skills☆ 3.4万2026年8月31日 更新
Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.
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。
mukul975/Anthropic-Cybersecurity-Skills☆ 3.4万2026年8月31日 更新
Synthesize user research into themes, insights, and recommendations. Use when you have interview transcripts, survey results, usability test notes, support tickets, or NPS responses that need to be distilled into patterns, user segments, and prioritized next steps.
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。
anthropics/knowledge-work-plugins☆ 3万2026年10月12日 更新
Answer data questions -- from quick lookups to full analyses. Use when looking up a single metric, investigating what's driving a trend or drop, comparing segments over time, or preparing a formal data report for stakeholders.
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。
anthropics/knowledge-work-plugins☆ 3万2026年10月12日 更新
Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on "design this clinical study", "what sample size", "R&D budget", "burn rate", "capitalize or expense", "TAM SAM SOM", "market sizing", "survey design", "segment the market", "plan user interviews", "usability test", "synthesize research insights". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns a digest. Distinct from ra-qm-team (regulatory submission), finance (corporate close/valuation), research/grants (funding discovery), product-team (persona/journey/live experiments), and marketing-skill (campaign analytics).
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。
alirezarezvani/claude-skills☆ 2.8万2026年8月30日 更新
Monitors customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models for SaaS customer success. Use when analyzing customer accounts, reviewing retention metrics, scoring at-risk customers, or when the user mentions churn, customer health scores, upsell opportunities, expansion revenue, retention analysis, or customer analytics. Runs three Python CLI tools to produce deterministic health scores, churn risk tiers, and prioritized expansion recommendations across Enterprise, Mid-Market, and SMB segments.
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。
alirezarezvani/claude-skills☆ 2.8万2026年8月30日 更新
Use when a Head of People Ops, BizOps lead, or Internal Communications owner needs to draft and sequence an internal-only change-management communication — a re-org announcement, a tool rollout, a policy change, a leadership transition, a layoff, an acquisition close, or an internal product launch — and the audience is employees (not customers). Pairs Prosci ADKAR and Kotter's 8-step change model with deterministic stdlib-only Python tools to produce a sequenced touchpoint calendar, a Kotter-compliant primary announcement, an audience-segmented FAQ, and manager cascade talking points; industry-tuned via --profile {tech-startup, scaleup, enterprise, public-company, non-profit}. Triggers on "all-hands announcement", "change comms", "rollout comms", "re-org announcement", "manager talking points", "layoff comms".
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。
alirezarezvani/claude-skills☆ 2.8万2026年8月30日 更新
Generate a Lean Canvas with problem, solution, metrics, cost structure, UVP, unfair advantage, channels, segments, and revenue. Use when exploring a lean startup canvas, testing a business hypothesis, or modeling a new venture.
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。
phuryn/pm-skills☆ 2.7万2026年10月10日 更新
Create a comprehensive product strategy using the 9-section Product Strategy Canvas — vision, segments, costs, value propositions, trade-offs, metrics, growth, capabilities, and defensibility. Use when building a product strategy, creating a strategic plan, or defining product direction.
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。
phuryn/pm-skills☆ 2.7万2026年10月10日 更新
Create refined user personas from research data — 3 personas with JTBD, pains, gains, and unexpected insights. Use when building personas from survey data, creating user profiles from research, or segmenting users for product decisions.
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。
phuryn/pm-skills☆ 2.7万2026年10月10日 更新
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying satisfaction 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。
phuryn/pm-skills☆ 2.7万2026年10月10日 更新
Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.
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。
phuryn/pm-skills☆ 2.7万2026年10月10日 更新
Create a lean, decision-ready Product Requirements Document with an 8-section template: summary, contacts, background, objective, market segments, value propositions (6-part JTBD template), solution, and release. Lean by default (about one to two pages), with a fuller spec on request. Use when writing a PRD, documenting product requirements, preparing a feature spec, or reviewing an existing PRD.
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。
phuryn/pm-skills☆ 2.7万2026年10月10日 更新
Weekly win-loss analysis for HubSpot closed deals. Reads deals closed-won and closed-lost in the trailing {{lookback_days}}-day window, breaks outcomes down by segment, competitor, price, and the stage lost deals die in, clusters close reasons into themes, and posts themes plus recommendations to {{alert_channel}}. Read-only and report-only — never writes to a HubSpot deal.
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。
kortix-ai/suna☆ 2万2026年10月13日 更新
Runbook for scoring and routing a new HubSpot lead to the right rep for {{projectName}} — territory matching, segment specialists, the stateless round-robin pool, intent scoring, HubSpot property writes, Slack notifications, and when to escalate an ambiguous lead to a human instead of guessing.
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。
kortix-ai/suna☆ 2万2026年10月13日 更新
AI audio editing pipeline: Whisper word-level transcription → Claude segment classification (KEEP/CUT_FILLER/CUT_FALSE_START/CUT_STUTTER/CUT_DEAD_AIR) → ffmpeg with 40ms qsin crossfades and room-tone fill → optional Cleanvoice cloud polish; plus GateScan/GateRepair for noise-gate ticking artifacts. Modes: --preview, --aggressive, --polish. Workflow: Clean. USE WHEN clean audio, edit audio, remove filler words, clean podcast, remove ums, cut dead air, polish audio, trim recording, cut stutters, ticking audio, clicking audio, audio clicks, gate artifacts, popping audio. NOT FOR video composition (use Remotion).
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。
danielmiessler/LifeOS☆ 1.9万2026年9月4日 更新
This skill should be used for book-to-SFT pipelines: ePub extraction, literary segmentation, author-voice dataset construction, style-transfer training, LoRA workflows, and model evaluation for voice replication.
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。
muratcankoylan/Agent-Skills-for-Context-Engineering☆ 1.8万2026年10月12日 更新
Automate customer engagement workflows including broadcast triggers, message analytics, segment management, and newsletter tracking through Customer.io via Composio
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。
composio-community/awesome-codex-skills☆ 1.7万2026年7月26日 更新
Wireless / 802.11 attack methodology for red team engagements and wireless security assessments. Covers monitor-mode setup, WPA/WPA2-PSK handshake capture and PMKID attacks, WPA3 SAE downgrade and Dragonblood, WPA-Enterprise (EAP) attacks (MSCHAPv2 cracking, EAP-TLS cert theft, evil-twin RADIUS), Karma / Known Beacons / Mana evil twin attacks, captive-portal phishing, KRACK and FragAttacks, WPS Pixie Dust, deauthentication and disassociation attacks, rogue AP construction (hostapd-mana), 802.1X bypass, MAC randomization defeat, BLE/Zigbee/IEEE 802.15.4 sidebands, and Wi-Fi 6/6E/7 considerations. Use when scoping wireless pentest, war-driving an estate, or testing corporate wireless segmentation.
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。
SnailSploit/Claude-Red☆ 7,4812026年10月13日 更新
This skill should be used when the user asks about Mixpanel product analytics, event data, funnel analysis, retention curves, cohort analysis, segmentation queries, user behavior, conversion rates, churn, DAU/MAU, ARPU, revenue metrics, feature adoption, A/B test results, user paths, flow analysis, or any request to query, explore, visualize, or analyze Mixpanel data using Python. Also use when the user asks to read, write, or manage Mixpanel "business context" — the markdown documentation that grounds AI assistants in an organization's structure and goals.
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。
openai/plugins☆ 7,4312026年10月8日 更新