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Found 1,906 Skills
Behavioral classification, performance analysis, and trading style detection for Solana wallets
Audit existing skills with Tessl scoring, metadata and trigger-coverage checks, repo conventions, and skill-authoring best practices. Use when creating or revising a skill, triaging weak self-activation, or comparing a skill against source-repo guidance such as `AGENTS.md`, `CLAUDE.md`, or repo rules, plus external skill guidance. Do not use to verify general application code or to rewrite unrelated docs.
Cross-model benchmark for gstack skills. Runs the same prompt through Claude, GPT (via Codex CLI), and Gemini side-by-side — compares latency, tokens, cost, and optionally quality via LLM judge. Answers "which model is actually best for this skill?" with data instead of vibes. Separate from /benchmark, which measures web page performance. Use when: "benchmark models", "compare models", "which model is best for X", "cross-model comparison", "model shootout". (gstack) Voice triggers (speech-to-text aliases): "compare models", "model shootout", "which model is best".
Walk through a complete GAIA benchmark→submit flow — from key resolution through HAL-compatible package generation
Use when conversation context is too long, hitting token limits, or responses are degrading. Compresses history while preserving critical information using anchored summarization and probe-based validation.
A safe calculator for mathematical expressions
Run Microsoft's eval-recipes benchmarks to validate amplihack improvements against baseline agents. Auto-activates when testing improvements, running evals, or benchmarking changes.
The industry standard library for machine learning in Python. Provides simple and efficient tools for predictive data analysis, covering classification, regression, clustering, dimensionality reduction, model selection, and preprocessing.
Multidisciplinary analytical engine using Charlie Munger's latticework of mental models. Applies cross-disciplinary thinking (math, physics, biology, psychology, economics) to dissect life and business decisions. Use when user presents a decision problem, investment question, or complex analysis request requiring deep rational analysis.
MLflow ML lifecycle management. Use for ML experiment tracking.
Researches investigative articles, interviews, and news coverage. Use when research needs journalistic sources for cross-referencing or additional context.
Copilot agent that assists with comprehensive QA strategy and test planning to ensure product quality through systematic testing and quality metrics Trigger terms: QA, quality assurance, test strategy, QA plan, quality metrics, test planning, quality gates, acceptance testing, regression testing Use when: User requests involve quality assurance tasks.