Skill UI

Monitors SaaS portfolios with Python CLI tools to score customer health, flag churn risk tiers, and prioritize expansion opportunities, suitable for retention reviews or account planning workflows.

This resource provides a minimal working example for implementing a complete digital document signing workflow using the Documenso SDK. It comprehensively guides users through creating a document, uploading a PDF file, adding designated recipients, placing specific signature fields, and finally triggering the signing process via code examples (TypeScript, Python) or REST API calls. Use this when integrating document signing into new applications or testing core document management capabilities.

This skill demonstrates how to use the Juicebox SDK to perform advanced people searches and profile enrichment. Users can search for individuals using natural language queries (e.g., "senior ML engineer at FAANG with PhD") and retrieve detailed contact information, skills, and education data for professional outreach and market research. Supports both TypeScript and Python.

Guides sales engineers through RFP/RFI analysis, competitive feature matrices, POC planning, demo prep, and proposal delivery using Python tooling and checkpoints to ensure coverage, differentiators, and win/loss insights.

An advanced skill for Scrum Masters that uses Python scripts to analyze raw sprint data exported from tools like Jira. It provides comprehensive insights including Monte Carlo velocity forecasting, a multi-dimensional team health score (0-100), and tracking of action items and recurring themes from retrospectives. Ideal for process improvement, sprint planning, and stakeholder reporting.

Models cap table dilution, SAFE conversion, and exit waterfalls for venture rounds, generating OCF inputs and running Python scripts to calculate ownership changes and waterfall outcomes.

Scans a company or sector for hiring, funding, product, team, market, and tech signals using CLAUDE web search and Python scoring to surface investment readiness, momentum, and competitive risks for VC deal sourcing.

Assistant for venture fund administrators: ingests capital calls, investments, and cash flows to compute KPIs (TVPI, DPI, IRR, MOIC), model carry/fees, and draft LP quarterly updates via Claude Code + Python.

Hard screening skill runs deterministic VC analyses where Claude gathers context, Python scores/formats, and the pipeline produces auditable verdicts with investment thesis guidance.

Performs TAM/SAM/SOM sizing via Claude-led research and Python computation while summarizing competitive landscapes and tech-stack maturity to support venture capital diligence.

This skill generates auditable market research reports and market sizing scenarios. It ensures every claim is traceable to primary sources, separating facts from estimates. Suitable for defining markets, analyzing competitive landscapes, and creating forecast models with sensitivity analysis. It supports Python-based workflows and LaTeX templates for professional documentation.