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Found 108 Skills
Project management expertise - agile methodology, estimation, risk management, stakeholder management
Show real token usage and estimated savings for the current session. Reads directly from the Claude Code session log — no AI estimation. Triggers on /caveman-stats. Output is injected by the mode-tracker hook; the model itself does not compute the numbers.
Estimate software development tasks accurately using various techniques. Use when planning sprints, roadmaps, or project timelines. Handles story points, t-shirt sizing, planning poker, and estimation best practices.
This skill should be used when the user asks to 'broadcast transaction', 'send tx', 'estimate gas', 'simulate transaction', 'check tx status', 'track my transaction', 'get gas price', 'gas limit', 'broadcast signed tx', or mentions broadcasting transactions, sending transactions on-chain, gas estimation, transaction simulation, tracking broadcast orders, or checking transaction status. Covers gas price, gas limit estimation, transaction simulation, transaction broadcasting, and order tracking across Solana, Ethereum, Base, BSC, Polygon, Arbitrum, and 20+ other chains. Do NOT use for swap quote or execution — use okx-dex-swap instead. Do NOT use for general programming questions about transaction handling.
Manages Amazon DocumentDB end-to-end — serverless-on-8.0 cluster setup, TLS/VPC/driver config, flexible-schema and vector-search data modeling, MongoDB compatibility assessment, DMS-based migration, slow-query diagnosis, major version upgrades (4.0→5.0→8.0), Well-Architected reviews (41-check wa_review.py), cost estimation, and security hardening. Retrieve for every DocumentDB question and when the user asks to set up or migrate MongoDB to AWS — DocumentDB is AWS's MongoDB-compatible managed database. Triggers: JSON document store, document database, MongoDB on AWS, Nested fields, Lambda cannot connect, TLS handshake, VPC port 27017, IAM auth, Secrets Manager, encryption at rest, $graphLookup, flexible schema, COLLSCAN, compound index, DMS migration, CDC cutover, $vectorSearch, RAG, Global Clusters, DR replication, cost sizing, audit, health check, production-readiness.
Apply event study methodology to measure abnormal returns and cumulative abnormal returns (CAR) around corporate or market events. Use this skill when the user needs to quantify the market impact of announcements, design event and estimation windows, or when they ask 'did this event affect stock price', 'how do I calculate abnormal returns', or 'what is the market reaction to this announcement'.
Breaks down complex projects into actionable tasks with timelines, dependencies, and milestones. Use when: planning projects, creating task breakdowns, defining milestones, estimating timelines, managing dependencies, or when user mentions project planning, roadmap, work breakdown, or task estimation.
CenterPose for keypoint / pose estimation. Detects object centers and regresses keypoint locations for 6-DoF object pose estimation. Use when training, evaluating, exporting, or running inference for a TAO CenterPose model. Trigger phrases include "train CenterPose", "6-DoF object pose", "keypoint estimation", "object pose regression".
Plan a sprint with capacity estimation, story selection, dependency mapping, and risk identification. Use when preparing for sprint planning, estimating team capacity, selecting stories, or balancing sprint scope against velocity.
Apply statistical methods to financial data including descriptive statistics, covariance estimation, regression, hypothesis testing, and resampling. Use when the user asks about return distributions, correlation between assets, building a covariance matrix, running a CAPM regression, testing whether alpha is significant, checking if returns are normal, or estimating confidence intervals. Also trigger when users mention 'volatility', 'how correlated are these', 'fat tails', 'skewness', 'R-squared', 'beta of a fund', 'bootstrap a Sharpe ratio', 'shrinkage estimator', 'Ledoit-Wolf', or ask why their optimizer produces unstable weights.
Integrate a HuggingFace Computer Vision model into the NVIDIA TAO Toolkit ecosystem (tao-core config, tao-pytorch trainer, tao-deploy TensorRT pipeline). Use when the user asks to "integrate a HuggingFace model into TAO", "add an HF model to TAO Toolkit", "wire a HuggingFace ViT/DETR/ SegFormer into tao-pytorch", "build a TAO trainer + deploy pipeline for an HF CV model", or pastes a HuggingFace model URL/ID and wants it turned into a TAO model. Covers the full 7-phase loop: prerequisites check, HuggingFace inspection and validation, codebase exploration, tao-core configuration and native trainer implementation, ONNX export plus TensorRT deploy integration, packaging and L0 testing, container-based end-to-end validation, and (conditional) accuracy/latency tuning. Supports classification, object detection, semantic / instance / panoptic segmentation, zero-shot detection, and depth estimation.
Conduct structured market research for a solopreneur business. Use when sizing a market, understanding industry dynamics, mapping the competitive landscape broadly, identifying trends, or building customer personas from external data. Covers TAM/SAM/SOM estimation, free data sources, trend analysis, and persona construction. Trigger on "research this market", "how big is this market", "understand the industry", "market trends", "who are the players in this space", "market analysis".