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Use Scapy, a Python library for working with network packets, to inspect saved captures or authorized live traffic. Summarize protocols and connections, identify suspicious patterns, craft test packets, and export findings as structured JSON reports.

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• Investigating saved network captures
• Summarizing traffic volumes, protocols, and connection endpoints
• Checking for SYN floods and DNS data leakage indicators

Deploy SageMaker endpoints, the services that answer model requests, with automatic capacity scaling, CloudWatch alarms, and resource tags. Supports real-time and asynchronous inference, scaling down to zero instances, deployment checks, and resource cleanup.

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• Deploying a real-time model endpoint
• Scaling a sparse workload down to zero instances
• Running long inference jobs asynchronously

Style UI for planetscale.com with extracted design tokens, named settings for colors, corner rounding, and fonts. Reuse the defined values and report missing settings when selecting the closest available alternative.

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• Style UI using values extracted from planetscale.com
• Align colors, corner rounding, and body fonts
• Identify gaps in the available style settings

Run an AWS Security Agent scan on the workspace — uploads the source to AWS, scans it with the managed Security Agent service, and returns ranked, verified findings with code locations and remediations. Use when the user asks to scan code, find vulnerabilities, run a security scan or review, check security issues, check scan status, show findings, list recent scans, or stop a scan.

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Turns one-shot external recon into a continuous monitoring program. Covers the scheduled re-scan-and-diff loop (baseline snapshot -> interval sleep -> re-scan -> asset/finding delta -> threshold-gated webhook alert), the scan-to-scan diff engine (new/removed/changed assets by a tracked-attribute table, new/resolved findings by a stable cross-scan fingerprint), adversary CTI / chatter monitoring across six public feeds (ransomwatch, ransomware.live, HackerNews Algolia search, Reddit security-subreddit RSS, GitHub Gist code-search, public Telegram channel scraping) with a source-kind-aware severity engine (leak-site/forum/telegram/paste tiers, CRITICAL through INFO), literal/glob/regex watchlist pattern matching, full-corpus capture with retroactive rescan on new watchlist entries, infrastructure-tracking-over-time discipline (certificate-transparency, passive-DNS, port/service, and typosquat re-enumeration cadence, and what a genuine 'perimeter drift' event looks like in the diff output), a five-state finding-lifecycle state machine (open/triaged/risk_accepted/resolved/false_positive) with per-severity SLA and fingerprint-based cross-scan dedup and auto-resolve/reopen rules, the alert-fatigue trap where a lifecycle-unaware rule re-fires on an already-accepted finding, a durable retry/backoff alert-outbox pattern ('queued is not delivered'), and copy-paste bash-cron plus PowerShell-Scheduled-Task recipes for a re-scan+diff loop with the Slack-compatible webhook payload shape. Passive OSINT and analysis only -- no new active-intrusion technique. Use when setting up ongoing monitoring for a retainer or MSSP engagement, tuning alert thresholds to avoid fatigue, triaging a finding's lifecycle status, investigating adversary chatter about a brand, building a 'what changed on the perimeter since last week' report, or deciding whether a persisting finding should re-alert.

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Use this skill when creating database schemas or tables for Timescale, TimescaleDB, TigerData, or Tiger Cloud, especially for time-series, IoT, metrics, events, or log data. Use this to improve the performance of any insert-heavy table. **Trigger when user asks to:** - Create or design SQL schemas/tables AND Timescale/TimescaleDB/TigerData/Tiger Cloud is available - Set up hypertables, compression, retention policies, or continuous aggregates - Configure partition columns, segment_by, order_by, or chunk intervals - Optimize time-series database performance or storage - Create tables for sensors, metrics, telemetry, events, or transaction logs **Keywords:** CREATE TABLE, hypertable, Timescale, TimescaleDB, time-series, IoT, metrics, sensor data, compression policy, continuous aggregates, columnstore, retention policy, chunk interval, segment_by, order_by Step-by-step instructions for hypertable creation, column selection, compression policies, retention, continuous aggregates, and indexes.

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Runs a security scan on a deployed Power Pages site, fetches the latest scan report, and produces a plain-language summary. Scans the live site's public surface for vulnerabilities and surfaces issues by severity. Use when the user wants to scan, check, test, audit, or assess a published site, find vulnerabilities on production, view the latest scan report, see previous scan results, run a security audit, or asks "how safe is my live site?", "is my site vulnerable?", "audit my production site" — even if they say "find issues" or "check for problems" without mentioning "scan" or "security".

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Perform advanced network scanning and service enumeration using Nmap for penetration testing and security assessments. Use this skill when conducting network reconnaissance, port scanning, service version detection, OS fingerprinting, and vulnerability scanning. Covers stealth scanning, firewall evasion, NSE script usage, and network mapping for infrastructure penetration tests.

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Set up CodeQL security scanning in GitHub Actions or with the local CLI. Get guidance on language settings, build steps, analysis rules, result uploads, and troubleshooting so you can configure scans and interpret their findings.

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• Adding security scans to GitHub Actions
• Running local scans with the CodeQL CLI
• Investigating failed builds or result uploads

Deploy and operate Falco to monitor running containers in Kubernetes or Docker. Choose a driver, validate detection rules, confirm alerts for suspicious activity, and forward those alerts to a central security monitoring system.

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• Installing Falco on a Kubernetes cluster
• Choosing a driver for the Linux environment
• Checking alerts for suspicious container activity

Analyze malicious JavaScript from phishing pages, payment data theft scripts, and malware downloaders. Unwrap encoded strings and nested execution layers to reveal hidden behavior, identify stolen data fields, and document suspicious destinations for incident response.

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• Analyzing obfuscated scripts on phishing pages
• Investigating payment data theft on checkout pages
• Examining JavaScript that downloads further malware

Build a central vulnerability dashboard with DefectDojo to combine scanner findings, remove duplicates, and track remediation. Includes Docker deployment, automated scan imports from CI/CD pipelines, Jira ticket integration, and API queries for reporting metrics.

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• Combining findings from multiple security scanners
• Importing scan results automatically from CI/CD pipelines
• Connecting vulnerability findings to Jira tickets

Design a security operations center escalation matrix that defines incident priorities, response deadlines, analyst responsibilities, and notification paths. Use business impact, asset importance, and data sensitivity to decide when incidents need senior or management attention.

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• Defining incident priorities and response deadlines
• Clarifying handoffs between analyst tiers
• Setting escalation rules for overdue incidents

Build a recurring vulnerability scanning process with Nessus, Qualys, or OpenVAS. Prioritize findings using asset importance and known exploitation, then organize remediation deadlines, monitoring dashboards, and automatic tickets for urgent issues.

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• Establish recurring infrastructure vulnerability scans
• Prioritize fixes using asset importance and exploitation data
• Track remediation deadlines and overdue findings

Analyze single-cell data with scvi-tools, using deep learning to combine datasets, correct differences between experiments, and transfer cell labels. Model guides and reusable scripts cover RNA, protein, chromatin accessibility, spatial data, and downstream analysis.

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• Integrate single-cell RNA datasets and correct batch effects
• Analyze paired RNA and protein or RNA and ATAC measurements
• Transfer cell-type labels from reference data

Check whether furniture occupies an available measured floor area in Pascal, including rotation, overlap, and required spacing. Receive a spatial report that separates verified floor fit from unverified height, door movement, and delivery conditions.

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• Checking a sofa against measured room dimensions
• Comparing furniture placement at different rotations
• Checking overlap and required walking space

Review Windows privilege escalation paths from a standard user session to Administrator or SYSTEM. Examine service permissions, token privileges, library loading, scheduled tasks, and stored credentials, with detection indicators for defensive validation.

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• Investigating privilege escalation in authorized Windows assessments
• Reviewing service and scheduled task permissions
• Checking detection coverage with attack and defense teams

Assess Docker, containerd, and Podman environments for weaknesses that could expose the host system. The skill organizes checks for excessive permissions, exposed runtime sockets, and known vulnerabilities, alongside indicators defenders can monitor.

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• Assessing container isolation
• Reviewing permissions and exposed runtime sockets
• Checking known runtime vulnerabilities

Set up NVIDIA infrastructure for synthetic data generation on MicroK8s or Azure AKS. Coordinate Kubernetes, inference services, and OSMO workflow execution, with prerequisite checks, deployment validation, capacity planning, and failure investigation before workloads are retried.

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• Set up a synthetic data generation environment on MicroK8s
• Deploy an Azure AKS environment with OSMO and inference services
• Check GPU quotas and capacity before scaling

Create starter projects for AI agents, add deployment configuration and automated build and release pipelines to existing projects, or update generated project files. Supports Python and Go ADK templates and a prototype-first approach.

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• Starting a Python or Go agent prototype
• Adding deployment configuration to an existing project
• Adding an automated build and release pipeline

Review EVM and Solana tokens for hidden minting, blocked sales, fee changes, and liquidity withdrawal risks. Combine code scanning with checks of privileged controls to identify mechanisms that could enable a rug pull, or issuer exit scam.

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• Reviewing token risks before an investment
• Checking Solana mint and freeze authorities
• Scanning token code for suspicious controls

Investigate Windows weaknesses that could let a standard user gain Administrator or SYSTEM access. Guides authorized penetration tests through system inspection, credential checks, escalation validation, and reports with remediation recommendations.

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• Investigating Windows privilege escalation paths
• Checking service permissions and stored credentials
• Assessing token privileges and missing patches

Guides single-cell RNA-seq analysis, which examines gene activity in individual cells. Covers data loading, quality checks, clustering, marker genes, cell type annotation, and plots, with AnnData handling and scVI/scANVI workflow planning.

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• Checking and filtering single-cell RNA-seq data
• Visualizing cell groups with UMAP or t-SNE
• Finding marker genes and annotating cell types

Generates a standalone YOLO26 detection and tracking service scaffold for VSS Search and Alerts. Includes DeepStream configuration, Docker files, and tests, with Kafka integration guidance and clear limits on validation before model assets are available.

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• Creating a standalone YOLO26 service for VSS
• Generating a scaffold before model assets are ready
• Checking Kafka integration with VSS workflows