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Persistent Agent Goal Loop Orchestration

sickn33/antigravity-awesome-skills

The /goal command converts standard agent prompts into persistent, self-correcting loops (plan → act → test → review → iterate). It is designed for long-running, complex engineering tasks like migrations, coverage lifts, or refactoring, ensuring progress is tracked against a verifiable stop condition and mandated documentation.

Define Cognitive Patterns For Agent Reasoning

cognitive-pattern

This tool enables the definition and management of structured cognitive patterns for advanced AI agents. It guides decision-making by codifying complex reasoning strategies, including decision trees, chain of thought (CoT), and analogy mapping. Use it to build robust, self-improving agents that can solve complex problems step-by-step and track their learning status.

Continuous Learning Behavioral Pattern Extractor

continuous-learning-v2

An advanced system that analyzes coding sessions via hooks to extract atomic, confidence-scored behaviors called "instincts." It tracks patterns, allowing users to evolve these instincts into comprehensive skills, commands, or agents. V2.1 introduces project-scoped learning, preventing knowledge contamination between different codebases and improving development workflow efficiency.

Cost-Aware LLM Pipeline

cost-aware-llm-pipeline

Pattern for controlling LLM API costs while preserving quality. Combines complexity-based model routing, immutable budget tracking, retry logic limited to transient failures, and prompt caching. Use when building LLM API apps, processing batches with varying difficulty, or enforcing budget guardrails in production.

Cost Tracking for AI Sessions

This tool automatically reads usage data from active AI coding sessions (JSONL format). It tallies token usage per model and tier, calculates the total cost in USD using specified pricing models, and persists a structured record into the cost-tracking namespace. Use this after completing a chunk of work or at the end of a session to provide accurate data for cost reporting and optimization.

GAIA Agent Benchmark Comparison and Gap Analysis

gaia-architecture-comparison

This skill provides a detailed, side-by-side comparison of advanced LLM agent evaluation frameworks, such as ruflo and HAL. It helps researchers and developers identify capability gaps—including real code execution, full web browsing, and structured file parsing—and prioritize architectural improvements for robust agent benchmarking and performance tracking.

Recursive Decision Ledger

recursive-decision-ledger

This skill manages repeated rollouts and recursive prompting by maintaining an append-only decision ledger. It tracks trials, marks, and coherence checks to prevent auto-approval of live trading or destructive actions. Ideal for high-dimensional search, stochastic optimization, and ensemble comparison requiring visible evidence trails.

AIHOT AI News & Updates

KKKKhazix/khazix-skills

Query Chinese AI industry news, hot topics, and daily reports via the AIHOT public API. Summarizes updates on models, products, and papers into a readable brief without requiring an API key. Provides real-time industry insights and event tracking.

RuView Advanced Model Training Pipeline

ruview-model-training

A comprehensive guide detailing the entire model lifecycle for RuView. It supports multiple advanced tracking methods including camera-free pose estimation (WiFlow), camera-supervised methods using MediaPipe, robust contrastive embeddings (RuVector), and domain generalization (MERIDIAN). Covers training, evaluation, and deployment across local GPU and cloud platforms.

Hotspot Monitoring

liyupi/yupi-hot-monitor

Search and analyze trending topics across Chinese and international sources like Bing, Google, HackerNews, Weibo, and Bilibili. Useful for tracking breaking news, monitoring keywords, and generating hotspot reports.

AAAI Submission Audit

aaai-submission

brycewang-stanford/Awesome-Journal-Skills

Audit an AAAI main technical track submission for OpenReview readiness, double-blind anonymity, page limits, reproducibility checklist, supplementary material, author limits, multiple-submission policy, and AAAI AI-use policy compliance.

AAMAS Submission Readiness Checklist

aamas-submission

brycewang-stanford/Awesome-Journal-Skills

This comprehensive guide provides a detailed audit checklist for authors submitting to the AAMAS conference. It covers verifying the correct conference track, maintaining double-blind anonymity, adhering to strict formatting rules (e.g., page limits, supplementary zip caps), and identifying potential submission-blocking risks to ensure readiness before the deadline.

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