Skills / variance-analysis / Alternatives

Data & Science · 12 alternatives

variance-analysis alternatives.

variance-analysis is decompose financial variances into drivers with narrative explanations and waterfall analysis. Use when analyzing budget vs. actual, period-over-period changes, revenue or expense variances, or preparing variance commentary for leadership. Below are the other data & science skills in the directory, with the most-starred repositories first. A proof means the skill was run on a fixed brief with and without it and both results are online, so you can judge the output rather than the star count.

The list

12 skills compared.

Interact with Slack workspaces using browser automation. Use when the user needs to check unread channels, navigate Slack, send messages, extract data, find information, search conversations, or automate any Slack task. Triggers include "check my Slack", "what channels have unreads", "send a message to", "search Slack for", "extract from Slack", "find who said", or any task requiring programmatic…

Source vercel-labs/agent-browserLicense Apache-2.0

Master binary analysis patterns including disassembly, decompilation, control flow analysis, and code pattern recognition. Use when analyzing executables, understanding compiled code, or performing static analysis on binaries.

Source wshobson/agentsLicense MIT

Analyze competition, identify differentiation opportunities, and develop winning market positioning strategies using Porter's Five Forces, Blue Ocean Strategy, and positioning maps. Use this skill when evaluating competitors, assessing market positioning, identifying sustainable competitive advantages, or preparing competitive strategy analysis for a startup or investor pitch.

Source wshobson/agentsLicense MIT

Prepare, format, and validate datasets for supervised fine-tuning and preference training. Use when converting raw data into training format, applying chat templates, configuring sequence packing, generating synthetic training data, or writing a dataset card before a run.

Source wshobson/agentsLicense MIT

Calculate TAM/SAM/SOM for market opportunities using top-down, bottom-up, and value theory methodologies. Use this skill when sizing markets, estimating addressable revenue, validating market opportunity for a new venture, or building investor-ready market analysis for a startup pitch or business plan.

Source wshobson/agentsLicense MIT

Master memory forensics techniques including memory acquisition, process analysis, and artifact extraction using Volatility and related tools. Use when analyzing memory dumps, investigating incidents, or performing malware analysis from RAM captures.

Source wshobson/agentsLicense MIT

Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.

Source wshobson/agentsLicense MIT

Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.

Source wshobson/agentsLicense MIT

Set up a working ML training/inference environment on NVIDIA DGX Spark (GB10, aarch64, CUDA 13). Use when installing PyTorch/Unsloth/TRL/vLLM on DGX Spark, hitting libcudart or wheel-ABI errors on aarch64, or choosing between NGC containers and bare pip installs.

Source wshobson/agentsLicense MIT

Manage unified memory and thermals during long-running ML jobs on NVIDIA DGX Spark. Use when planning memory headroom for a training run on GB10, when a job OOMs on unified memory, or when monitoring temperature and power during multi-hour training.

Source wshobson/agentsLicense MIT

Preflight and diagnose the ten known failure modes for ML training on NVIDIA DGX Spark. Use when a training run on DGX Spark fails to start, OOMs below the 128GB limit, slows down mid-run, or before any multi-hour training job on GB10.

Source wshobson/agentsLicense MIT

Build comprehensive 3-5 year financial models with revenue projections, cost structures, cash flow analysis, and scenario planning for early-stage startups. Use this skill when creating financial projections, calculating burn rate or runway, modeling fundraising scenarios, or preparing investor-ready financials for a seed or Series A raise.

Source wshobson/agentsLicense MIT

Skills belong to their authors. Descriptions are taken from each SKILL.md, star counts from the source repository, and nothing here is paid placement. See the whole category: best data & science skills.