Data & Analytics

Execute KQL queries and analyze data in Azure Data Explorer for log analytics, telemetry, and time series insights. Execute KQL queries against massive datasets with sub-second performance, including filtering, aggregation, time series analysis, and cross-table joins Discover and explore cluster resources, databases, and table schemas to understand your data model before querying Supports five core query patterns: basic retrieval, aggregation analysis, time series analytics, join-based correlation, and schema discovery Built-in fallback to Azure CLI commands when MCP tools timeout or encounter connection errors

Identify cost savings across Azure subscriptions through resource analysis, utilization metrics, and actionable optimization recommendations. Discovers orphaned resources (unattached disks, unused NICs, idle gateways) and over-provisioned services using Azure Quick Review Queries actual costs from Azure Cost Management API and utilization data from Azure Monitor to support rightsizing recommendations Generates prioritized optimization reports with estimated savings, implementation commands, and Azure Portal links for each resource Includes specialized Redis cost optimization analysis with subscription filtering and pre-built report templates Requires Cost Management Reader, Monitoring Reader, and Reader roles; validates prerequisites before analysis begins

日程待办摘要：编排 calendar +agenda 和 task +get-my-tasks，生成指定日期的日程与未完成任务摘要。适用于了解今天/明天/本周的安排。

Unified Azure cost management: query historical costs, forecast future spending, and optimize to reduce waste. WHEN: \"Azure costs\", \"Azure spending\",…

Query metrics, logs, and traces across Azure Monitor, Application Insights, and Log Analytics. Access metrics, KQL log queries, and distributed tracing through MCP tools or Azure CLI commands Supports Application Insights for APM and performance analysis, Log Analytics for custom KQL queries, and Azure Monitor for infrastructure metrics Includes common KQL query patterns for errors, request performance, and resource usage monitoring Workbooks integration for building interactive observability dashboards and reports

飞书 OKR：管理目标与关键结果。查看和编辑 OKR 周期、目标（Objective）、关键结果（Key Result）、对齐关系、量化指标和进展记录。当用户需要查看或创建 OKR、管理目标和关键结果、查看对齐关系时使用。

Create, edit, and analyze Excel spreadsheets with formulas, formatting, and error-free calculations. Supports reading, creating, and modifying .xlsx, .xlsm, .csv, and .tsv files using pandas for data analysis and openpyxl for formulas and formatting Automatically recalculates all formulas and scans for Excel errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?) using LibreOffice integration Enforces industry-standard color coding and number formatting for financial models (blue for inputs, black for formulas, green for internal links, red for external links) Includes comprehensive documentation requirements for hardcoded values and assumption-based formula construction to maintain dynamic, updateable spreadsheets

Install the lark-okr skill for your AI agent. Published on open.feishu.cn.

When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google…

Expert analysis and actionable recommendations to improve marketing page conversion rates. Analyzes pages across seven dimensions: value proposition clarity, headline effectiveness, CTA placement, visual hierarchy, trust signals, objection handling, and friction points Provides structured output with quick wins, high-impact changes, test ideas, and copy alternatives for headlines and CTAs Includes page-type-specific frameworks for homepages, landing pages, pricing pages, feature pages, and blog posts Reads product marketing context from .agents/product-marketing-context.md if available to inform recommendations without redundant questions

Strategy, optimization, and execution for paid advertising campaigns across Google Ads, Meta, LinkedIn, and other platforms. Covers campaign structure, audience targeting, bidding strategies, and creative best practices across five major ad platforms with platform-specific strengths and use cases Includes funnel-based retargeting strategies, segmentation by stage, and exclusion rules to prevent wasted spend on existing customers Provides optimization frameworks for high CPA, low CTR, and high CPM scenarios, plus weekly reporting metrics and attribution considerations Offers naming conventions, budget allocation guidance for testing vs. scaling phases, and pre-launch checklists to ensure proper conversion tracking and setup

Optimize post-signup user activation and time-to-value through structured onboarding flows. Defines activation metrics and "aha moments" specific to your product type, then maps the fastest path from signup to first value Provides templates for onboarding checklists, empty states, and guided tours designed to reduce friction and guide users to core features Includes trigger-based email coordination strategies to reinforce in-app actions and re-engage stalled users across days 1, 3, 7, and beyond Offers funnel analysis frameworks to identify drop-off points and prioritize fixes by impact, plus experiment ideas for flow simplification and progress mechanics

Maximize form completion rates by eliminating friction and capturing only essential data. Identifies completion killers: each field reduces completion by 10-25%, so every field must justify its necessity before, during, or after submission Covers all non-signup form types: lead capture, contact, demo request, application, survey, checkout, and quote request forms with type-specific guidance Provides field-by-field optimization strategies including label clarity, validation, error messaging, and mobile keyboard handling Includes multi-step form patterns with progress indicators, progressive commitment sequencing, and conditional field logic for complex forms Offers 20+ A/B test hypotheses across layout, copy, trust elements, and mobile UX with expected conversion impacts

Expert guidance for designing statistically valid A/B tests and experiments. Provides a structured hypothesis framework, sample size calculations, and metrics selection (primary, secondary, guardrail) to ensure rigorous test design Covers test types (A/B, A/B/n, MVT, split URL), traffic allocation strategies, and implementation approaches (client-side vs. server-side) Includes pre-launch checklists, guidance on avoiding common pitfalls like early peeking, and frameworks for analyzing results with statistical significance Helps determine baseline requirements, minimum detectable effect, and test duration based on traffic volume and conversion rates

Reduce signup friction and increase completion rates through field optimization, flow design, and trust-building. Guides field-by-field optimization covering email, password, name, social auth, and deferrable fields like company or role Covers single-step vs. multi-step flow decisions with progressive commitment patterns and mobile-specific best practices Includes audit framework for identifying drop-off points, error handling strategies, and post-submit experience design Provides 20+ experiment templates for testing layout, authentication options, copy variations, and trial mechanics

Popup and modal optimization for conversion without user friction or brand damage. Covers seven popup types: email capture, lead magnets, discounts, exit intent, announcements, slide-ins, and feedback modals, each with specific copy and design formulas Includes five trigger strategies (time-based, scroll, exit intent, click, behavior) with guidance on when each works best and typical performance benchmarks Provides design best practices for desktop and mobile, including sizing, close button placement, visual hierarchy, and accessibility requirements Offers A/B testing frameworks across placement, triggers, messaging, personalization, and frequency capping to identify optimal configurations Emphasizes timing, clear value proposition, and respecting user choice as core principles to avoid annoying interruptions

Reduce voluntary and involuntary churn through cancel flows, dynamic save offers, and payment recovery. Design exit surveys and targeted save offers (discounts, pauses, downgrades) matched to cancellation reasons, typically recovering 25-35% of at-risk customers Implement proactive retention by tracking health signals (login frequency, feature usage, support sentiment) and intervening before customers reach the cancel page Set up dunning sequences with smart payment retries, escalating emails, and grace periods to recover 50-60% of failed payments Integrates with Stripe, Chargebee, Paddle, and retention platforms like Churnkey and ProsperStack for end-to-end churn prevention

Design and optimize systems connecting marketing, sales, and customer success into a unified revenue engine. Covers lead lifecycle stages (Subscriber → Lead → MQL → SQL → Opportunity → Customer), stage definitions with entry/exit criteria, and ownership accountability across teams Includes lead scoring frameworks combining fit (ICP attributes) and engagement (behavioral signals) with negative scoring to filter unqualified leads Provides lead routing methods (round-robin, territory, account-based, skill-based) with speed-to-lead optimization and SLA enforcement for handoffs Details pipeline stage hygiene, required fields per stage, stale deal detection, and key metrics (conversion rates, velocity, coverage ratio, win rate by source) Covers CRM automation workflows, deal desk approval tiers, data dedup and enrichment strategies, and quarterly audit checklists