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Found 946 Skills
MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".
Security best practices and vulnerability prevention for Golang. Covers injection (SQL, command, XSS), cryptography, filesystem safety, network security, cookies, secrets management, memory safety, and logging. Apply when writing, reviewing, or auditing Go code for security, or when working on any risky code involving crypto, I/O, secrets management, user input handling, or authentication. Includes configuration of security tools.
Expert knowledge for Azure Backup development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when backing up Azure VMs, AKS, SQL/PostgreSQL/MySQL, SAP HANA, files/disks/blobs, or automating via CLI/PowerShell/REST, and other Azure Backup related development tasks. Not for Azure Site Recovery (use azure-site-recovery), Azure Virtual Machines (use azure-virtual-machines), Azure Blob Storage (use azure-blob-storage), Azure Files (use azure-files).
Describe your sales, marketing, or GTM objective and get routed to the right skill. Use when: 'write a cold email', 'prep for a discovery call', 'handle this objection', 'build a prospecting list', 'help with my pitch', 'write a proposal', 'plan outreach', 'research this account', 'forecast pipeline', 'create GTM content', 'audit my SEO', 'write landing page copy', 'brainstorm marketing ideas', 'plan content strategy', 'design pricing page', 'edit marketing copy', 'apply marketing psychology', 'A/B test', 'ad creative', 'AI SEO', 'analytics', 'churn', 'cold email', 'competitor page', 'CRO', 'email sequence', 'lead magnets', 'launch', 'onboarding', 'paid ads', 'popups', 'programmatic SEO', 'referral', 'revops', 'sales enablement', 'schema markup', 'signup flow', 'site architecture', 'social media', 'GEO', 'generative engine optimization', 'Product Hunt', 'Reddit research', 'image generation', 'logo', 'banner', 'tweets', 'domain name', 'demand research', 'knowledge archive', 'Qwilr proposal', 'Qwilr quote', 'Qwilr deal room', 'Qwilr API', 'Qwilr webhook', 'Qwilr template', 'interactive proposal', 'proposal analytics', 'proposal engagement', 'digital sales room', 'connect Qwilr to CRM', 'Salesloft', 'cadence', 'sequence', 'call review', 'call coaching', 'call score', 'deal health', 'deal risk', 'deal review', 'MEDDPICC', 'forecast', 'pipeline coverage', 'Rhythm', 'Conversations', 'Drift', 'Apollo', 'Apollo.io', 'prospect list', 'find leads', 'build a list', 'enrich contacts', 'find emails', 'clean CRM data', 'buying signals', 'intent data', 'job changes', 'lead scoring', 'deliverability', 'Apollo sequence', 'Apollo credits', 'competitive displacement', 'win away', 'steal customers', 'takeout list', 'buying committee', 'multi-thread', 'stakeholder map', 'account map', 'MQL', 'SQL', 'PQL', 'scoring model', 'lead score', 'Mailshake', 'Lead Catcher', 'email deliverability', 'warmup', 'SPF', 'DKIM', 'DMARC', 'lead routing', 'lead assignment', 'round-robin', 'territory routing', 'webhook', 'integration', 'Zapier', 'Make', 'data sync', 'Smartlead', 'SmartSenders', 'SmartInfra', 'SmartAgents', 'SmartDialer', 'SmartDelivery', 'SmartProspect', 'unlimited mailboxes', 'agency outbound', 'multi-client', 'white label', 'client outbound', 'Lemlist', 'lemlist', 'Lemwarm', 'lemwarm', 'Lemlist sequence', 'Lemlist multichannel', 'People Database', 'Yesware', 'Yesware campaign', 'Yesware tracking', 'email tracking', 'open tracking', 'click tracking', 'attachment tracking', 'tracking pixel', 'Apple MPP', 'Mixmax', 'Mixmax sequences', 'Mixmax tracking', 'Mixmax scheduling', 'Mixmax rules', 'Mixmax dialer', 'Mixmax AI', 'Reply.io', 'Reply.io sequences', 'Reply.io warmup', 'Reply.io Jason AI', 'Reply.io deliverability', 'Reply.io agency', 'Woodpecker', 'Woodpecker campaigns', 'Woodpecker warmup', 'Woodpecker deliverability', 'Woodpecker agency', 'Woodpecker Bounce Shield', 'meeting scheduler', 'booking link', 'round-robin scheduling', 'no-show', 'Calendly', 'Chili Piper', 'Groove', 'Groove.cm', 'GrooveFunnels', 'GroovePages', 'GrooveSell', 'GrooveMail', 'GrooveAffiliate', 'GrooveMember', 'GrooveVideo', 'GrooveWebinar', 'GrooveBlog', 'GrooveKart', 'sales funnel', 'funnel builder', 'landing page funnel', 'upsell', 'downsell', 'order bump', 'email marketing', 'broadcast email', 'nurture sequence', 'welcome sequence', 'opt-in email', 'affiliate program', 'affiliate commission', 'referral program', 'webinar selling', 'evergreen webinar', 'automated webinar', 'membership site', 'online course', 'course platform', 'drip content', 'checkout page', 'checkout optimization', 'cart abandonment', 'payment plan'.
Audit de sécurité couvrant l'authentification, l'injection SQL, l'exposition de secrets, le CSRF et les vulnérabilités du Top 10 OWASP.
Add a Docker dev service to this project. Supported services: Redis, RabbitMQ, PostgreSQL, MySQL/MariaDB, MongoDB. Writes Docker Compose and Taskfile configs to .devtools/.
Migrates databases between providers (Postgres, MySQL, Supabase, PlanetScale, MongoDB). Reads source schema, generates migration scripts, handles data type mapping, foreign keys, indexes, triggers, stored procedures. Validates migration with row counts and checksums. Generates migration-plan.md with step-by-step execution guide, rollback procedures, estimated downtime.
Designs and builds ETL/ELT data pipelines. Takes data sources, destination, transformation requirements. Generates pipeline code (Python/SQL), scheduling config, error handling, monitoring setup, and data quality checks. Outputs data-pipeline-spec.md + implementation files.
Use when deploying a database to Zeabur. Use when user needs MySQL, PostgreSQL, MongoDB, or Redis. Use when user says "I need a database", "add database", "deploy postgres", "set up MySQL", "add Redis", "add MongoDB", or "connect to database". Also use when user mentions data persistence issues like "data lost after restart", "data not saved", "data disappears", "need persistent storage for data", or "how to persist data". Also use when integrating a database with an existing service.
Use when running commands inside a Zeabur service container. Use for one-off database operations like queries, data cleanup, or migrations (e.g. mongosh, psql, mysql, redis-cli). Use when user says "exec into container", "run command in service", "query database", "delete from database", "run mongo command", "run SQL", "check files in container", "debug inside service", or "shell into service". Use for container-level debugging like checking env vars, files, processes, or connectivity. NOT for deploying databases (use zeabur-template-deploy instead).
Use when working with ANY data persistence, database, storage, CloudKit, migration, or serialization. Covers SwiftData, Core Data, GRDB, SQLite, CloudKit sync, file storage, Codable, migrations.
This skill guides the use of Jupyter notebooks for data analysis, exploration, and visualization, particularly with BigQuery. It outlines best practices for notebook execution and validation (supporting both cell-by-cell execution and full notebook generation depending on tool availability), library installation, and structuring notebooks for clarity. It also covers specific rules for data cleaning, plotting, and integrating with BigQuery SQL and machine learning workflows. Relevant when any of the following conditions are true: 1. The user request involves a data analysis, data exploration, data visualization, or data insights task that requires multiple steps, queries, or visualizations to answer. 2. The user explicitly requests a notebook (.ipynb). 3. You are creating, editing, or executing cells in a Jupyter notebook. 4. You need to query BigQuery from within a notebook. DO NOT use the Python BigQuery client library; instead, you MUST use the `%%bqsql` magics explained in this skill.