Skill UI

Streamline Microsoft Clarity analytics exports inside Claude Code via the Composio integration, fetching heatmaps, session metrics, and engagement data segmented by browser, device, location, source, medium, campaign, channel, or URL over the last 1-3 days.

This skill provides advanced techniques for optimizing PostHog Cloud usage and reducing associated costs. It covers auditing event volume, implementing intelligent event sampling (e.g., sampling pageviews or autocapture events), filtering bot traffic, and tuning session recording rates. The goal is to maintain critical analytical value while staying within budget limits.

This tool provides comprehensive network traffic analysis capabilities by querying the Arkime API. Users can search sessions, download PCAPs for forensics, detect sophisticated threats like C2 beaconing (via jitter/interval analysis), spot DNS tunneling patterns, and flag connections to known-bad TLS certificate issuers. Ideal for security assessment and incident investigation.

This comprehensive guide details techniques for performing forensic investigations on Linux systems. It covers analyzing critical logs—including auth.log, syslog, systemd journal, and auditd—to reconstruct user sessions, trace unauthorized access, detect privilege escalation, and establish detailed event timelines following a suspected security compromise.

bdistill transforms AI interactions into a structured, queryable knowledge base. It extracts, structures, and quality-scores domain knowledge from both closed-source AI models (in-session) and local open-source models (via Ollama). Users can build comprehensive reference datasets, Q&A pairs, or generate structured training data for traditional machine learning, ensuring validated and exportable domain expertise.

This guide provides production-ready patterns for integrating with Bright Data proxy services. It covers critical aspects like setting up a proxy client, implementing robust retry logic for transient errors (e.g., 502, 503), managing sticky sessions for consistent IPs, and parsing complex HTML responses. Essential for building reliable, high-scale web scrapers using TypeScript and Python.

A dedicated skill for performing manual data synchronization and knowledge recall with OpenViking. It allows users to explicitly trigger chat transcript syncing from OpenClaw sessions and perform targeted memory searches via command line, without disrupting normal conversation flow or occupying the standard context engine slot.

Execute arbitrary PySpark or pure Python code directly on Fabric Spark compute using the Livy API. This method creates ephemeral sessions without generating persistent notebook artifacts. It provides full read/write access to lakehouse Delta tables, making it ideal for agent-driven ETL pipelines, quick data transformations, or analyses where session cleanup is critical. Users must manage the session lifecycle (create, run, and delete).

A comprehensive guide for threat hunters focusing on detecting stolen session cookies and OAuth/PRT token replay (T1550.001). This skill teaches correlation techniques across Microsoft Entra ID SigninLogs and Okta System Logs, enabling the detection of impossible travel, refresh-token reuse, and anomalous lateral movement within federated SaaS environments. Essential for post-phishing or post-compromise investigations.

This tool performs robust outlier detection on individual session spending. Utilizing Median and Median Absolute Deviation (MAD), it calculates a modified z-score, making it highly resistant to extreme values, unlike mean+sigma methods. It specifically identifies which singular sessions are anomalous, making it crucial for cost monitoring, auditing, and integrating into CI/CD pipelines to prevent unexpected resource overruns.

This skill provides a granular, session-by-session view of total accumulated costs. It lists metrics such as start time, message count, top model, and total cost for every recorded conversation. This is ideal for identifying which specific sessions consumed the most resources, which is crucial for project retrospectives and evaluating the sustainability of current session patterns.

This tool provides a granular, per-message cost breakdown within a single conversation session. It serves as a deep-dive utility following an anomaly detection, allowing operators to pinpoint exactly which messages incurred the highest costs. It reveals critical cost components like output tokens, cache writes, and model escalations, helping users understand the true resource consumption beyond simple token counts.