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Found 1,946 Skills
Ann — Master Orchestrator for MEL/SRHR work. Use when Ane brings any analytical, evaluation, SRHR, or structured-output task. Ann classifies task complexity, queries the MEL Wiki, retrieves knowledge, creates an implementation plan (verifies with user for complex tasks), delegates to Vi for execution, runs a 5-point quality gate, and delivers. General-purpose — not tied to any specific project.
Use Sifta for candidate sourcing, candidate search, and public profile enrichment in vertical recruitment scenarios for the AI industry. This skill is intended for users looking to find, screen, enrich, or evaluate AI engineers/developers, embodied intelligence talents, solopreneurs/independent developers, founders, AI product managers, GTM/GMT/global expansion/AI marketing talents, and research-focused paper talents. This skill is NOT applicable to general talent search outside these personas, company intelligence, sales leads, outreach, ATS, KOL collaborations, or general web research.
You are **Test Results Analyzer**, an expert test analysis specialist who focuses on comprehensive test result evaluation, quality metrics analysis, and actionable insight generation from testing a...
Builds production AI/ML systems — model training, fine-tuning, MLOps pipelines, model serving, evaluation frameworks, RAG optimization, and agent orchestration at scale. Use when the user asks to build, train, or deploy ML models, set up MLOps pipelines, optimize RAG systems, create inference endpoints, or design production AI agents.
When the user wants to build a free tool for marketing — lead generation, SEO value, or brand awareness. Use when they mention 'engineering as marketing,' 'free tool,' 'calculator,' 'generator,' 'checker,' 'grader,' 'marketing tool,' 'lead gen tool,' 'build something for traffic,' 'interactive tool,' or 'free resource.' Covers idea evaluation, tool design, and launch strategy. For pure SEO content strategy (no tool), use seo-audit or content-strategy instead.
Design and evaluate vaccine candidates using computational immunology tools. Covers epitope prediction (MHC-I/II binding via IEDB), population coverage analysis, antigen selection, adjuvant matching, and immunogenicity assessment. Integrates IEDB for epitope prediction, UniProt for antigen sequences, PDB/AlphaFold for structural epitopes, BVBRC for pathogen proteomes, and literature for clinical precedent. Use when asked about vaccine design, epitope prediction, immunogenicity, MHC binding, T-cell epitopes, B-cell epitopes, or population coverage for vaccine candidates.
Use when evaluating ideas in voting phase. Be aggressive - score misaligned or poor ideas low enough to veto, score weak proposals below approval, score strong aligned ideas high. First check directive, then vote.
Build macroeconomic and rates dashboards combining macro indicators, yield curves, inflation breakevens, and swap rates. Use when monitoring macro conditions, analyzing yield curve shape, decomposing real vs nominal rates, assessing policy rate expectations, or evaluating financial conditions.
Analyze the bond futures basis by pricing futures, identifying the cheapest-to-deliver, and comparing with yield curves to assess delivery option value and basis trading opportunities. Use when analyzing bond futures, computing the basis, identifying CTD bonds, calculating implied repo rates, or evaluating basis trades.
Tests authentication and authorization mechanisms in mobile application APIs to identify broken authentication, insecure token management, session fixation, privilege escalation, and IDOR vulnerabilities. Use when performing API security assessments against mobile app backends, testing JWT implementations, evaluating OAuth flows, or assessing session management. Activates for requests involving mobile API auth testing, token security assessment, OAuth mobile flow testing, or API authorization bypass.
Guide the understanding and management of trade settlement and clearing processes. Use when designing settlement workflows for T+1 compliance, understanding DTC/NSCC/FICC clearing infrastructure, analyzing continuous net settlement (CNS) netting obligations, setting up institutional trade processing (affirmation, confirmation, allocation, matching), investigating settlement fails and designing fail reduction programs, implementing buy-in procedures under Reg SHO Rule 204, assessing corporate action impact on pending settlements, evaluating DVP/RVP mechanics for institutional deliveries, handling when-issued or as-of trades, or managing settlement bank relationships and intraday liquidity. Also covers FX funding gaps for cross-border T+1 settlement.
Machine-learning prediction strategy framework via Longbridge Securities — walk-forward rolling training with feature engineering (MACD, RSI, Bollinger Band width, volume change rate) and a scikit-learn classifier (Random Forest / Gradient Boosting); retrains every 60 days, predicts 5-day direction; buy signal when probability > 0.6, sell when < 0.4; evaluates win rate, profit factor, and Sharpe ratio. Triggers: "机器学习", "ML策略", "预测模型", "随机森林", "梯度提升", "深度学习", "AI选股", "walk-forward", "機器學習", "ML策略", "預測模型", "隨機森林", "梯度提升", "machine learning", "ML strategy", "predictive model", "random forest", "gradient boosting", "AI stock selection", "walk-forward", "rolling training", "feature engineering", "scikit-learn", "XGBoost".