Skill UI

This meta-skill automates the process of compiling a daily briefing on the top submissions from the arXiv repository. It fetches the latest papers in a specified category, generates a structured, per-paper digest summarizing the core claims, methods, and key findings. It then renders this information into a professional PowerPoint deck (one slide per paper) and persists the entire digest into long-term memory. Ideal for daily research briefings or knowledge management.

This meta-skill provides an auditable workflow for professional compliance self-assessments (e.g., GDPR, SOC2). It executes deep research while retaining citation evidence, then compiles the findings into a comprehensive package: a signable DOCX report, a read-only PDF archive for permanence, and a persistent memory note to guarantee the evidence chain is recallable. Ideal for structured policy auditing.

A meta-skill designed to generate a comprehensive daily operating brief. It intelligently combines structured data from pasted context (calendars, tasks, emails), user memory (priorities, open loops), and external factors like weather, providing a holistic and actionable plan for the day. Ideal for users needing a single, high-level summary of their commitments and priorities.

This meta-skill automatically inspects open GitHub Pull Requests, failing CI runs, and new issues. It utilizes the GitHub API to gather critical updates and summarizes the findings into three actionable buckets (To Review, Awaiting Me, CI Red). Finally, it persists follow-up tasks to long-term memory, helping developers efficiently prioritize their daily workflow.

This meta-skill provides a complete pipeline to bootstrap a domain knowledge base from any single seed input (URL, PDF, Git repository, or free text). It automatically classifies the source type, ingests the content using a multi-search engine, persists the summary to memory, and finally generates a structured XLSX index file, making the information immediately searchable and usable.

A meta-skill designed to monitor long-running processes, such as model fine-tunes or CI builds, executed within a detached tmux session. It captures output, automatically uses a sub-agent to diagnose failures, proposes a fix, and records the complete debugging process to memory. Ideal for intermittent failure debugging and continuous integration pipelines.

This meta-skill automates the creation of a comprehensive daily morning digest. It retrieves the user's local weather forecast, gathers news articles on a specified topic, generates a structured summary from both sources, and finally saves this digest into long-term memory for future recall. Ideal for starting the day with key information.

This meta-skill automates the entire process of transforming raw Excel data into structured business insights. It reads the raw data, performs advanced trend and anomaly analysis, writes the resulting findings to a dedicated 'Insights' sheet, and persists key performance indicators (KPIs) to long-term memory. Ideal for comprehensive business reviews and data-driven decision-making.

SkillOpt-Sleep simulates an agent's nightly 'sleep' cycle to continuously improve performance without requiring model retraining. It harvests historical sessions, mines recurring tasks, and replays them offline. Learning and insights are then consolidated into the agent's memory and skills (CLAUDE.md/SKILL.md), proposing bounded, validated edits that the user must explicitly adopt, ensuring measurable, sustained improvement over time.

This skill provides a comprehensive guide for building scalable Retrieval-Augmented Generation (RAG) pipelines and persistent agent memory using Pinecone as the vector database. It covers index setup, embedding large corpuses, implementing dense and hybrid semantic search, and advanced metadata filtering for real-world production systems. Use this for building searchable knowledge bases and context-aware AI agents.

Atlas Ledger is a critical companion designed to provide lasting 'memory' to project contracts. It automatically processes detected deviations or 'drift' (e.g., from audits or reviews) and distills these instances into formal, actionable contract clauses (WHEN/DON'T/INSTEAD). These clauses are written to a persistent project memory file, Atlas.md. This mechanism ensures that lessons learned from failure are systematically captured, allowing future contract cycles to incorporate these rules, thereby strengthening overall project governance and reliability.

This skill guides coding agents through a comprehensive memory loop using AccInt's MCP server. It allows agents to retrieve prior outcomes, resolve complex reasoning frames, and formally close commitments with verifiable evidence (e.g., passing tests, successful merges). Essential for managing non-trivial, multi-step development workflows and ensuring work builds on genuine results.