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Found 1,954 Skills
Use historical analogies to inform strategic decisions by identifying structural similarities and differences between past and present situations. Use this skill when the user draws on historical precedent to justify a strategy, needs to evaluate whether a historical comparison is valid, or wants to learn from past events — even if they say 'this is like the dotcom bubble', 'history repeats itself', or 'what can we learn from how X handled this'.
Apply mechanism design (reverse game theory) to engineer incentive-compatible rules for allocation problems. Use this skill when the user needs to design auctions, voting systems, or matching markets, or when evaluating whether a proposed mechanism satisfies incentive compatibility and individual rationality constraints.
Design and implement smart contracts as self-executing programmatic agreements on blockchain. Use this skill when the user needs to build automated on-chain logic, evaluate smart contract security, or design tokenized business rules — even if they say 'smart contract development', 'automated agreement', or 'on-chain logic'.
Evaluate the performance of Triton operators on Ascend NPU. It is used when users need to analyze operator performance bottlenecks, collect and compare operator performance using msprof/msprof op, diagnose Memory-Bound/Compute-Bound bottlenecks, measure hardware utilization metrics, and generate performance evaluation reports.
Convin platform help — AI-powered contact center QA, coaching, and conversation intelligence. Use when setting up Convin automated QA scoring, Convin Real-Time Assist not surfacing prompts, Convin transcription missing speakers or inaccurate with accents, Convin audits hanging or calls delayed on dashboard, Convin AI Phone Call agent for outbound, Convin LMS agent training, or evaluating Convin vs Observe.AI vs Cresta vs Balto vs Enthu.AI for contact center QA. Do NOT use for CCaaS platform selection (use /sales-ccaas-selection) or building a coaching program (use /sales-coaching).
Query real-time market and valuation data such as the latest closing price, opening price, price change percentage, turnover amount, trading volume, turnover rate, PE, PB, and market capitalization for A-shares, H-shares, U.S. stocks, and their indices. Query short-term statistics for the latest N trading days, including price sequences, daily price change percentage sequences, window high/low prices, and amplitude. Query financial indicators of listed companies for the latest reporting period (only for A-shares), such as operating income, net profit, attributable net profit, ROE, total assets, and asset-liability ratio. Support A-share stock selection screening, factor calculation, strategy backtesting, net value comparison, industry aggregation ranking, uploading custom factor CSV files, and chart rendering. Currently, H-shares and U.S. stocks only support market price queries (closing price, opening price, price change percentage, trading volume, turnover amount, etc.). Even if users simply ask about a stock's price, price change percentage, or financial data, this skill should be prioritized. Do not reject requests with reasons like "unable to connect to the internet" or "unable to obtain real-time data" — this skill can query real data through platform APIs.
Direct visual and creative work for campaigns, photography, illustration, video, and branded experiences. Use this skill whenever the user wants to brief a photographer, direct illustrators, plan a creative campaign, develop visual concepts, write a creative direction document, or evaluate creative work for fit. Triggers on art direction, photo brief, photography brief, illustration brief, campaign concept, creative concept, visual direction, mood board, look and feel, visual treatment, video direction. Also triggers when the user has approved brand identity but needs to extend it into specific creative deliverables.
Amazon Ads deep analysis covering Sponsored Products, Sponsored Brands (incl. Sponsored Brands Video), Sponsored Display (audiences + contextual), and basic Amazon DSP. Evaluates campaign structure, ACOS/TACOS targets, search-term harvesting, negative keyword discipline, Brand Analytics signals, day-parting, bid management, auto vs manual campaign mix, ASIN targeting, and DSP retargeting. Use when user says Amazon Ads, Amazon advertising, Amazon PPC, Amazon search ads, Sponsored Products, Sponsored Brands, Sponsored Display, Amazon DSP, ACOS, TACOS, retail media audit, Amazon Marketing Services, AMS, or Amazon seller advertising.
Apply trader Serenity's (@aleabitoreddit) AI/semiconductor supply-chain analytical lens to US-stock ideas and market judgment. Use this skill whenever evaluating a stock decision (buy / sell / hold / size); forming an outlook on any AI, semiconductor, optical/CPO, memory, power/grid, or neocloud name; mentioning any ticker in Serenity's universe (NBIS, AXTI, LITE, SIVE, COHR, AAOI, IREN, CRWV, MU, SNDK, NVDA, TSM, MRVL, AVGO, INTC, SOI, IQE, TSEM, CIFR, XLU, VST, CEG, EWY, etc.); asking "what would Serenity think", "is this a real bottleneck", or wanting a supply-chain / bottleneck read on a thesis. Decision-support only — never auto-trades and never places or cancels orders.
PyTorch-based TAO image classification. Supports a wide range of backbones (FAN, EfficientNet, ResNet, etc.) with distillation and quantization for deployment. Use when training, evaluating, distilling, quantizing, exporting, or running inference for a TAO image-classification (PyT) model. Trigger phrases include "train image classifier", "TAO classification", "ResNet/EfficientNet/FAN backbone classifier", "classification-pyt".
Token integration and implementation analyzer based on Trail of Bits' token integration checklist. Analyzes token implementations for ERC20/ERC721 conformity, checks for 20+ weird token patterns, assesses contract composition and owner privileges, performs on-chain scarcity analysis, and evaluates how protocols handle non-standard tokens. Context-aware for both token implementations and token integrations.
Expert in designing effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when: prompt engineering, system prompt, few-shot, chain of thought, prompt design.