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F# Testing Patterns and Best Practices

Comprehensive patterns and tools for writing robust tests for F# applications within the modern .NET ecosystem. This guide covers unit testing (xUnit, FsUnit), property-based testing (FsCheck), mocking dependencies (NSubstitute), and full integration testing (WebApplicationFactory). Ideal for improving test coverage, validating complex business logic, and establishing a resilient testing infrastructure.

GAIA Benchmark Failure Debugging Tool

This skill provides a systematic workflow for diagnosing failures in GAIA benchmark runs. Users can analyze task traces, classify failure modes (e.g., Tool Gap, Reasoning Miss, Extraction Bug), identify root causes, and apply targeted fixes to improve AI agent performance. It is essential for optimizing LLM benchmarks and finding performance regressions.

GAIA Benchmark Submission Pipeline

gaia-submission

Guides users through the entire end-to-end process of running the GAIA benchmark. It covers environment validation, cost estimation, model execution, and generating a signed, HAL-compatible submission package for leaderboards. This ensures high integrity and reproducibility for model performance evaluation.

Geometric Design System Guidelines

bergside/awesome-design-skills

A comprehensive framework for creating structured, clean, and highly accessible design systems. It defines foundational constraints, typography scales, color tokens, and component-level rules, ensuring consistency and usability across engineering and design teams. Focuses on achieving WCAG 2.2 AA compliance and implementation readiness.

GitHub Repository Operations Automation

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.

Deep Multi-Source Research Synthesis

sickn33/antigravity-awesome-skills

This advanced workflow is designed to generate comprehensive, fact-checked research reports on any complex topic. It systematically performs fan-out web searches across multiple defined angles, fetches multiple sources, and employs a rigorous adversarial verification system (3-vote) to validate claims. The final output is a highly cited, synthesized report, ideal for academic or critical business research.

GOAP: Goal-Oriented Planning Engine

A comprehensive framework for creating and executing intelligent, goal-oriented action plans (GOAP). This system analyzes preconditions, optimizes costs, and provides adaptive replanning capabilities. It is designed for complex objectives that require multiple, dependent steps, ensuring robust task completion even when unexpected state changes occur.

Manage Benchmarking Suites For Evolution

A utility for scaffolding and verifying fixed evaluation corpora (bench suites). It generates deterministic test suites from existing repositories, decoupling the evaluation process from the repo's natural test suite. This ensures consistent fitness scoring when running evolution pipelines across different commits or forks.

Detect Structural Drift From Audit History

harness-drift-from-history

This tool simplifies the process of detecting structural drift by combining audit listing, fresh auditing, and trend diffing into a single command. It finds the most recent audit record, runs a current audit against the repository, and compares the two using structural similarity metrics. It alerts when the structural distance falls below a specified threshold, helping maintain code consistency over time.

Repo Readiness Genome Report

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.

Run GEPA Learning Cycle For Policy Optimization

This tool executes a GEPA learning cycle, automating the evolution and optimization of policy prompts against a scored task corpus. Instead of relying on manual prompt iteration, it measures performance improvements, identifying the best working 'harness genome.' It is ideal for measuring sustainable improvements in task performance and supports a free, cost-estimating dry-run mode before committing to actual model calls.

Scaffold Custom AI Agent Harnesses

A powerful tool designed to scaffold sophisticated, custom AI agent harnesses using the metaharness CLI. It supports various templates (e.g., coding, devops, marketing) and AI hosts (e.g., Claude, Codex). Crucially, it operates with maximum safety, defaulting to a dry-run mode and refusing to write to the calling repository root, ensuring controlled and predictable development workflows.

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