Analytics & Monitoring Agent Skills for Perplexity

Train sparse autoencoders to interpret model features.

Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas…

Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure…

Set up, audit, and debug analytics tracking implementation — GA4, Google Tag Manager, event taxonomy, conversion tracking, and data quality.

Use when reviewing or rebalancing direct vs. partner-led channel economics — computing fully-loaded cost-to-serve per channel, channel ROI…

Chief Data Officer advisory for startups: AI training data rights and consent provenance, data product strategy (warehouse vs lakehouse vs…

Use when building a quarterly bookings forecast, ARR projection, pipeline forecast, NRR projection, or commit/best-case/pipe-only board…

Revenue leadership for B2B SaaS companies.

Router/index for the 2 finance skills bundled in this plugin: financial-analyst (ratio analysis, DCF valuation, budget variance, rolling…

Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making.

Use proactively whenever LLM API costs come up -- or should.

Use when doing upstream market-research methodology — sizing a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single…

Cross-functional organizational health check combining signals from all C-suite roles.

Systematic performance profiling for Node.js, Python, and Go applications.

Use when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing…

Use when the user asks to design a RAG pipeline, choose a chunking strategy or embedding model, pick a vector database, or evaluate…

SaaS financial health advisor. Use when a user shares revenue or customer numbers, or mentions ARR, MRR, churn, LTV, CAC, NRR, or asks how…

World-class senior data scientist skill specialising in statistical modeling, experiment design, causal inference, and predictive analytics.

ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs.

Use when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality…

Scan codebases for technical debt, score severity, track trends, and generate prioritized remediation plans.