cohort-analysis
Perform cohort analysis on user engagement data. Identify retention trends, feature adoption rates, churn patterns, and generate actionable research recommendations through quantitative data analysis.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
189 skills found
Perform cohort analysis on user engagement data. Identify retention trends, feature adoption rates, churn patterns, and generate actionable research recommendations through quantitative data analysis.
Standardized detective skill integration for agent roles. Maps agents to code-analysis skills and enforces claudemem usage for memory-indexed code investigation.
Activates Prometheus planning mode for structured requirement gathering, codebase research, and task planning within Claude Code.
Master the EARS format to transform ambiguous feature ideas into precise, testable requirements, acceptance criteria, and edge case documentation.
Enable long-running, multi-session autonomous development tasks with state tracking, resumable execution, and dual-agent planning-execution workflows.
GitHub operations via gh CLI. Use for repository inspection, issues, PRs, releases, and deep codebase analysis including cloning for architectural insights.
Automated migration guide for Kotlin Multiplatform (KMP) projects upgrading to Android Gradle Plugin (AGP) 9.0+, covering plugin replacement, DSL updates, and project structure restructuring.
Find similar vulnerabilities and bugs across codebases using pattern-based analysis. Use when hunting bug variants, building CodeQL/Semgrep queries, or performing systematic code audits.
Analyze codebases to generate evidence-grounded Loa artifacts using Enterprise-Grade Managed Scaffolding for structured reality mapping.
Complete project architecture and structure guide for LobeHub. Use for codebase exploration, project organization, file location, and architectural context.
Generate optimized SQL queries from natural language. Supports BigQuery, PostgreSQL, MySQL, and Snowflake. Analyze database schemas, interpret business requirements, and output ready-to-run queries with explanations.
Identify, categorize, and troubleshoot flaky tests by analyzing CI history, execution patterns, and code structure to improve test suite reliability.