Skill UI

This tool analyzes Git diffs to provide comprehensive insights for Pull Requests (PRs) and large code changes. It calculates risk scores based on churn history and sensitive areas, classifies changes (e.g., feature, bugfix), recommends required reviewers, and provides detailed statistics. Use this before merging to assess code quality and minimize deployment risk.

This skill acts as an expert guide, transforming a complex, natural language workflow description (e.g., "build an MVP") into a structured, multi-step execution blueprint using ECC command groups. It identifies the necessary command sequence, the logical run-order, and crucial stop conditions (e.g., max iterations, review passes). It is advisory and designed for planning, filling the gap between flat documentation and single-prompt output.

A formal framework designed for evaluating AI-assisted code generation sessions. It implements Development Oriented Evals (EDD) principles, allowing users to define capability and regression criteria. The system supports multiple evaluation types—code-based, model-based, and human review—and tracks reliability using advanced metrics like pass@k, ensuring robust quality control for AI agents.

A comprehensive, library-agnostic checklist covering best practices for Flutter and Dart applications. It guides developers on architectural principles, state management patterns (BLoC, Riverpod, etc.), Dart idioms, performance optimization, and clean code principles, making it invaluable for code reviews.

This skill provides comprehensive automation for managing GitHub workflows across the entire development lifecycle. It covers detailed issue triage, PR review status checks, CI/CD failure debugging, official release management, and security monitoring using the GitHub CLI. Ideal for maintaining open-source project health and streamlining team development processes.

A comprehensive 7-section readiness report generated for a repository, analyzing key metrics including risk score, test confidence, and publish readiness. It assesses architectural viability, agent topology recommendations, and potential risks, making it essential for pre-mint reviews, CI/CD gating, and detecting architectural drift in large codebases.

This skill generates an enterprise-grade threat model report using the `harness threat-model` command. It categorizes threats across the MCP surface, providing a detailed report including the overall worst severity (clean, low, medium, high) and specific findings. Ideal for pre-launch security reviews and periodic audits when sharing findings with an InfoSec team.

This skill generates a structured, non-advisory worksheet for planning trade ideas, basket adjustments, or comparing prediction markets. It helps users methodically review venues, underliers, constraints, and manual execution steps without placing any trades or providing financial advice. Ideal for the research phase of quantitative finance workflows.

This skill guides the design and rigorous review of goal-oriented agent feedback loops. It helps ensure that complex autonomous multi-step agents are robust, preventing failures such as infinite looping, goal-gaming, or running to completion with incorrect assumptions. It covers defining machine-decidable goals, setting boundaries, and selecting the correct loop type (servo, regulator).

This tool orchestrates the end-to-end process of building a brand-new feature. It automates the entire lifecycle, including initial research, planning, Test-Driven Development (TDD) implementation, code review, and gated commit. Use this when adding a capability that does not currently exist in the system.

This advanced orchestration tool streamlines the process of building a Minimum Viable Product (MVP). By ingesting high-level design documents (SDD/PRD), it automatically plans thin, end-to-end vertical slices. The system then scaffolds, executes TDD implementation, and manages gated commits, transforming theoretical specifications into a functional, reviewable starting point, dramatically accelerating initial development cycles.

This tool is designed to manage the process of altering an existing, functional feature to meet a new desired specification. It ensures a structured workflow: first, update the existing test cases to reflect the new behavior; second, modify the underlying implementation to pass these updated tests; finally, complete through review and gated commit. Use this when the feature works but its behavior needs adjustment.