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Build detections for fileless attacks on Windows using process activity, script logs, and endpoint monitoring. Investigate suspicious PowerShell, code injected into running processes, WMI persistence, and registry-based execution with logging guidance and detection query examples.

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• Building detections for suspicious PowerShell activity
• Hunting for code injection into running processes
• Monitoring WMI persistence and registry-based execution

Investigate Windows malware that runs in memory or abuses legitimate system tools. Use logs, registry entries, and memory dumps to trace persistence, identify suspicious activity, and produce detection rules and an analysis report.

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• Investigating suspicious PowerShell activity
• Checking WMI persistence mechanisms
• Finding malicious code in memory dumps

Respond to security incidents across AWS, Azure, and GCP by investigating audit logs, containing compromised identities, isolating resources, and preserving evidence. Organize recovery and follow-up security measures for credential leaks, unauthorized permission changes, and attacks spanning cloud services.

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• Responding to leaked cloud credentials
• Investigating unauthorized permission or resource changes
• Preserving audit logs and disk snapshots

Examine NTFS disk images for residual or hidden data beyond standard file recovery. Analyze file metadata, change records, unused space within allocated storage, and Alternate Data Streams to reconstruct available activity and identify suspicious timestamp differences.

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• Find residual data in file slack space
• Investigate metadata left by deleted files
• Reconstruct recorded file changes

Analyze captured RAM with Volatility to investigate suspicious processes, injected code, network connections, and other evidence of compromise. The skill guides memory investigations and organizes findings into timelines and reports, including malware traces absent from disk.

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• Investigating fileless malware after an endpoint alert
• Finding hidden processes and injected code
• Linking suspicious processes to network connections

Analyze NTFS file records and change journals to investigate deleted files on Windows disks. Recover surviving metadata and content where possible, reconstruct file activity timelines, and compare timestamps for signs of deliberate manipulation.

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• Recovering names and paths of deleted files
• Assessing whether deleted file content can be recovered
• Reconstructing file creation, modification, and deletion timelines

Turn a project idea into a detailed system plan before coding. Organize architecture, data flows, dependencies, and file-level tasks in a linked Markdown workspace, with research references, consistency checks, and saved state for resuming later.

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• Plan a new system before writing code
• Break implementation into tasks with files and dependencies
• Check a design for gaps and contradictions

Analyze large logs, test results, API responses, and files outside the conversation, then return focused findings. It guides agents to save, process, index, and search outputs while limiting how much raw data enters their working context.

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• Extracting errors from large logs
• Summarizing test failures and build warnings
• Inspecting JSON and CSV data

Add an iMessage channel to NanoClaw so you can message an agent. Choose a local Mac account or a hosted photon.codes line, with setup guidance for permissions, device login, and channel registration.

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• Chat with a NanoClaw agent through iMessage
• Connect the iMessage account on a Mac
• Set up hosted iMessage on a non-Mac system

Save research findings, fixes, and decisions in a shared Markdown notebook on disk. Search and organize notes across sessions, record when they inform actual work, and let unused notes expire automatically.

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• Saving research findings for future sessions
• Reusing fixes for difficult bugs
• Recording design decisions and their reasoning

Prepare and troubleshoot cmux releases by collecting changelog entries, updating versions, checking release readiness, and publishing tags. Follow requirements for macOS disk images, signing, notarization, and update feeds that guide installed apps to new versions.

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• Preparing a new cmux release
• Collecting changelog entries from merged PRs
• Troubleshooting a failed pre-tag check

Keep plans, research findings, and progress in Markdown files for complex agent work. Separate task plans and automatic planning reminders help the agent recover saved context, track decisions, and identify the next action.

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• Resuming long research tasks
• Tracking phases and the next action
• Separating plans for concurrent tasks

Organize multi-step research and project work with Markdown files for plans, findings, and progress. Gemini hooks, automatic actions at session events, surface planning context so the agent can resume from saved records.

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• Resuming research after a break
• Tracking project phases and decisions
• Recording errors and test results

Keep plans, research findings, and progress in Markdown files for multi-step work in Kiro. Read saved project records when resuming a task to recover goals, decisions, and recent actions.

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• Organizing findings during extended research
• Tracking a refactor across multiple phases
• Resuming work after a long break

Organize multi-step research and project work in Continue using Markdown files for plans, findings, and progress. When invoked, the skill reads saved planning context to support resuming work and reviewing earlier decisions.

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• Resuming interrupted work in Continue
• Recording findings during research
• Tracking project phases and decisions

Manage files in Google Cloud's Cloud Storage buckets, the containers that hold stored data. Upload, download, and organize content, configure access and time-limited sharing links, and manage storage lifecycle, costs, and data protection.

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• Upload, download, and organize stored files
• Share files through time-limited signed URLs
• Review storage classes and lifecycle rules

Browse and search files on Google Cloud Filestore, read selected log lines, and inspect permissions and timestamps. Uses a Cloud Run bridge or an existing virtual machine without requiring local NFS client packages or root access.

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• Explore the folder structure of a Filestore share
• Find backup files by filename pattern
• Search remote logs for errors and read selected lines

Use a computer connected to Kortix to read and write files, run shell commands, and operate desktop apps. The skill covers machine selection, access checks, screen inspection, and handling connection or permission errors.

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• Reading and editing files on a connected computer
• Running commands on a selected laptop or server
• Clicking and typing in desktop applications

Evaluate a machine learning GPU cluster during a cloud trial or acceptance test. Measure GPU computing performance, communication within and between machines, and local and shared storage, then compile the results into a dated Markdown report.

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• Evaluating trial GPU machines from a cloud provider
• Running acceptance tests for a GPU cluster
• Measuring GPU performance under load from neighboring GPUs

Inspect Mac performance to find processes using excessive CPU, GPU, memory, or energy. Combine measurements with explanations of known system processes to diagnose slowness, heat, and startup load, then recommend actions without changing system settings.

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• Find the cause of a slow Mac
• Investigate loud fans and overheating
• Check memory pressure and swap activity

Combine all service research reports for a selected date into a local Markdown digest. Add up to five highlights to help maintainers prioritize updates, review proposed changes, and spot research errors.

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• Summarizing a day's service research
• Highlighting updates that need review
• Refreshing a digest after more research

Adds an explicit permission step before an agent deletes files or directories. It covers shell commands and deletion scripts, groups multiple files into one request, and requires the agent to stop when permission is denied.

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• Confirming permission before deleting files
• Reviewing multiple deletions in one request
• Adding approval steps to cleanup scripts

Diagnose slow systems, crashes, and resource problems on servers, PCs, virtual machines, and containers. Quick checks identify affected components, while deeper analysis investigates causes and provides optimization advice or repair plans.

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• Investigating a slow server or PC
• Finding causes of high CPU or low memory
• Checking disk space and network problems

Continue Python tasks when sandbox execution fails by saving code as a script and running it through run_shell. The workflow covers dependencies, execution checks, and output verification for PDFs, image processing, data analysis, and file operations.

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• Continuing Python tasks after sandbox initialization failures
• Generating PDFs from a saved script
• Running image processing or data analysis through the shell