performance-analyzer

Email teams can make costly decisions from underpowered or poorly controlled tests. This skill creates a structured experiment plan and interprets results using user-provided campaign data.

Email exports often mix active subscribers, lapsed customers, and people who must not receive messages. This skill converts your own exported data into documented segments and a suppression list with clear confidence labels.

Paid campaigns can lose relevance when the ad promise does not match the landing page. This skill checks the visitor experience and provides a clear pass, partial, or fix list.

Campaign teams need clear controls to prevent ads from appearing in unsuitable placements. This skill creates an evidence-backed exclusion plan and packages the material for an A1 brand-safety review.

Revenue-only conversion values can make value-based bidding optimize for low-margin orders. This skill creates a documented conversion-value model and QA checklist using margin, COGS, and defensible proxy values.

Subscribers may unsubscribe when messages arrive too often or cover unwanted topics. This skill designs clear topic, cadence, and pause choices that preserve a direct full opt-out path.

Trading strategy tests often overstate performance because they ignore bias, costs, and validation discipline. This skill guides Claude, Codex, and Claude Code through robust backtesting patterns.

Toutiao research often requires separate lookups for articles, videos, users, and comments. This skill routes those requests through MaxHub and returns concise bilingual results.

Finding suitable YouTube creators requires slow, repetitive profile research. This skill runs a BrowserAct workflow and returns channel metrics, links, and available contact details.

Xiaohongshu research is slow when teams inspect posts manually. This skill searches public notes, sorts results, and returns structured outputs for review.

Scientific datasets often arrive in specialized formats that are hard to inspect quickly. This skill detects the format, summarizes contents, checks quality, and produces a clear EDA report.

Single-cell RNA-seq workflows require careful QC, normalization, clustering, and documentation. This skill gives Scanpy workflows, scripts, templates, and references for reproducible analysis.