Skill UI

A comprehensive tool designed to audit the quality, relevance, and redundancy of all Claude skills and commands. It supports two modes: a rapid incremental scan for recently changed skills, and a deep full stocktake using AI judgment and expert checklists to assess viability (Keep, Improve, Update, Retire, Merge).

This tool initializes a structured multi-agent swarm with built-in anti-drift configuration. It is designed for orchestrating complex, multi-file tasks that require coordinated efforts from three or more specialized AI agents, such as feature implementation, cross-module refactoring, or comprehensive security audits. It supports various topologies (hierarchical, mesh, etc.) to ensure robust and manageable parallel work execution across large teams.

This skill calculates model interpretability for algorithmic trading signals using PageRank. It constructs a feature-contribution graph from an LSTM or Transformer signal and executes a single-entry PageRank calculation. The result identifies the top-K features that most significantly drove the prediction, providing a "regulator-grade" audit trail essential for compliance with regulations like the EU AI Act.

This skill performs mean-variance portfolio optimization by solving the linear system Σ · x = μ using the Conjugate Gradient (CG) method. It is significantly faster (40-60x) and numerically robust compared to legacy methods like the Neumann series. It takes a covariance matrix (Σ) and expected return vector (μ) to determine optimal asset weights, providing full provenance tracking for auditability.

Tree Ring Memory is a local-first, framework-agnostic layer for managing durable knowledge in AI agents. It provides structured methods for recalling past decisions, recording evidence, auditing project state, and deliberately forgetting information, ensuring the core project memory remains clean and actionable without relying on raw conversation transcripts.

Manages the creation and orchestration of complex, multi-step workflows. Supports two powerful methods: persistent MCP templates for human-gated, resumable pipelines, or native JavaScript scripts for advanced, programmatic agent fan-out. Ideal for complex business logic such as auditing, research, or multi-stage data processing.

This skill provides a comprehensive, read-only audit of a development workspace, including active repositories, installed plugins, connected services, and environment configurations. It analyzes existing capabilities against best practices to identify functional gaps and recommends the most valuable ECC-native skills, hooks, and workflows needed to enhance the development experience. Ideal for setup planning and architectural reviews.

This skill is designed to audit and critique existing skill packages for their readiness, safety boundaries, resource efficiency, and evidence quality. It helps users diagnose concrete issues, such as incorrect triggers or insufficient evidence, and suggests improvements without applying any changes. Use it when you need a comprehensive audit or quality grade for a published skill.

This skill executes a rigorous, deterministic integrity forensic audit using an external, pinned Anti-Autoresearch framework. It sweeps the submitted paper to detect potential inconsistencies, rule violations, and structural anomalies. The resulting verdict is converted into a typed policy gate (BLOCK/WARN/NO_NEW_BLOCKER) and an append-only obligations ledger, providing a final layer of assurance before submission or publication.

This tool performs a comprehensive audit of the project's stored auto-memory. It analyzes learned knowledge to identify actionable patterns for promotion to core rules, flag stale or outdated entries, and suggest opportunities for consolidating redundant knowledge. Use it after major development phases or when the memory knowledge base becomes crowded to maintain system knowledge quality.

An advanced, secure skill leveraging OpenAI Codex and GPT models for end-to-end software development tasks. It supports autonomous code implementation, complex bug fixing, architectural analysis, and rigorous code/plan review. Operating in a controlled sandbox environment, it adheres to least privilege principles, allowing users to delegate entire coding workflows, from feature development to security auditing, without manual intervention on every step. Ideal for developers needing full-cycle automation assistance.

A comprehensive, human-guided onboarding skill designed for users new to AI coding agents and Power BI agentic development. It provides structured setup help, deep conceptual explanations, and conversational guidance, mimicking a mentor's session. Modes include concise setup assistance and deep conceptual learning. Use cases: Setting up a new agent environment, understanding core AI concepts (models, prompts, tools), or auditing existing agent configurations.