Skill UI

This skill wraps the `getCompactContext` functionality to efficiently retrieve a compacted ReasoningBank context, specifically optimized for cost-analysis queries. It generates a detailed report summarizing critical metrics such as tokens saved, memories retrieved, and agentic-flow availability. It is essential for monitoring and optimizing resource usage in complex AI workflows, providing deep visibility into the efficiency and cost of the context retrieval mechanism.

This skill monitors federation spend events per peer using rolling windows (1h/24h/7d) and checks suspension thresholds. It aggregates cost data to verify budget circuit breakers before opening traffic or during periodic checks. It reads events from the federation-spend namespace and reports per-peer usage statistics.

This tool generates a detailed cost report, tracking token usage and associated USD costs across all AI agents and models. It provides crucial insights into budget utilization, breaking down spending by model (e.g., Opus, Sonnet), agent, and operational tier (Tier 1/2/3), helping teams manage spending and optimize resource allocation.

Provides a stable, single-call interface to dump all operational cost data. This includes total spending, usage per model tier, budget status, top sessions, and federation aggregates. Output is reliable JSON or Markdown, making it ideal for other plugins, automated dashboards, or programmatic consumption.

Reads the active Claude Code session jsonl, tallies per-model token usage, computes USD cost using reference pricing, and persists a structured record to the cost-tracking AgentDB namespace for reporting and optimization.

This skill analyzes and reports on the token usage, expenditure, and budget for AI models (like Claude Code) by querying a local SQLite database. It is essential for users who need detailed financial accountability, tracking costs by project, tool, or date, and managing operational budgets.

This tool provides a comprehensive overview of your project's memory usage across all associated memory systems. It reports metrics such as line counts, topic file counts, capacity limits, stale entries, and actionable recommendations to help maintain memory integrity and optimize performance.

This tool generates a detailed, local 'receipt' or impact report of all Claude Code activity recorded in local session transcripts. It cross-references this data with your local Git history to provide a quantifiable measure of effort and project contribution. Ideal for performance reviews, budget justifications, or self-auditing usage.

A read-only macOS and Windows storage analysis assistant that scans disk usage, classifies large items by cleanup risk, and generates an interactive HTML report with copyable commands for safe cleanup decisions.

This guide provides expert principles for designing and auditing system-level experiments in computer architecture (e.g., for ASPLOS-level conferences). It details the proper usage of various instruments—from real silicon and FPGAs to cycle-level simulators and analytical models—ensuring that every claim is matched to a valid, stated error model. It emphasizes workload selection, establishing strong baselines, performing rigorous ablation studies, and honestly reporting measurement noise and limitations to maintain scientific credibility.

A comprehensive guide for strengthening the reproducibility of academic papers, especially those involving systems claims (e.g., power usage, latency). It details maintaining a 'recipe ledger' for all reported metrics, ensuring constraint-aware measurement of environmental variables, and managing data/artifact consistency across the entire two-round revision process.

Comprehensive guide for using Gemini Notebook (formerly Google NotebookLM) via the nlm CLI and MCP server. Covers notebook creation, plan usage checks, source addition, content generation (podcasts, reports, quizzes, flashcards, etc.), research, and automation workflows. Essential for programmatic interaction with Gemini Notebook.