Agent Skills Directory

Revenue leadership for B2B SaaS companies. Revenue forecasting, sales model design, pricing strategy, net revenue retention, and sales team scaling. Use when designing the revenue engine, setting quotas, modeling NRR, evaluating pricing, building board forecasts, or when user mentions CRO, chief revenue officer, revenue strategy, sales model, ARR growth, NRR, expansion revenue, churn, pricing strategy, or sales capacity.

Monitors customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models for SaaS customer success. Use when analyzing customer accounts, reviewing retention metrics, scoring at-risk customers, or when the user mentions churn, customer health scores, upsell opportunities, expansion revenue, retention analysis, or customer analytics. Runs three Python CLI tools to produce deterministic health scores, churn risk tiers, and prioritized expansion recommendations across Enterprise, Mid-Market, and SMB segments.

Research a prospect then draft personalized outreach. Uses web research by default, supercharged with enrichment and CRM. Trigger with "draft outreach to [person/company]", "write cold email to [prospect]", "reach out to [name]".

Google Workspace administration via the gws CLI. Install, authenticate, and automate Gmail, Drive, Sheets, Calendar, Docs, Chat, and Tasks. Run security audits, execute 43 built-in recipes, and use 10 persona bundles. Use for Google Workspace admin, gws CLI setup, Gmail automation, Drive management, or Calendar scheduling.

Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results.

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.

Generate a daily or weekly digest of activity across all connected sources. Use when catching up after time away, starting the day and wanting a summary of mentions and action items, or reviewing a week's decisions and document updates grouped by project.

Analyzes RFP/RFI responses for coverage gaps, builds competitive feature comparison matrices, and plans proof-of-concept (POC) engagements for pre-sales engineering. Use when responding to RFPs, bids, or proposal requests; comparing product features against competitors; planning or scoring a customer POC or sales demo; preparing a technical proposal; or performing win/loss competitor analysis. Handles tasks described as 'RFP response', 'bid response', 'proposal response', 'competitor comparison', 'feature matrix', 'POC planning', 'sales demo prep', or 'pre-sales engineering'.

When the user wants to write, improve, or build a sequence of B2B cold outreach emails to prospects who haven't asked to hear from them. Use when the user mentions 'cold email,' 'cold outreach,' 'prospecting emails,' 'SDR emails,' 'sales emails,' 'first touch email,' 'follow-up sequence,' or 'email prospecting.' Also use when they share an email draft that sounds too sales-y and needs to be humanized. Distinct from email-sequence (lifecycle/nurture to opted-in subscribers) — this is unsolicited outreach to new prospects. NOT for lifecycle emails, newsletters, or drip campaigns (use email-sequence).

Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization. Use when analyzing sales pipeline coverage, forecasting revenue, evaluating go-to-market performance, reviewing sales metrics, assessing pipeline analysis, tracking forecast accuracy with MAPE, calculating GTM efficiency, or measuring sales efficiency and unit economics for SaaS teams.

Package an escalation for engineering, product, or leadership with full context. Use when a bug needs engineering attention beyond normal support, multiple customers report the same issue, a customer is threatening to churn, or an issue has sat unresolved past its SLA.

Multi-source research on a customer question or topic with source attribution. Use when a customer asks something you need to look up, investigating whether a bug has been reported before, checking what was previously told to a specific account, or gathering background before drafting a response.