Use when bumping Meteor package versions for beta, RC, or official releases. Covers the two version schemes (meteor-tool vs all other packages), the update-semver automation tool, manual files the tool does not handle, modern-tool npm package semver analysis, the official installer gate, and the full lifecycle from beta through official release. Applies to packages/*/package.js, scripts/admin/, npm-packages/meteor-installer/, modern-tool npm packages, and .meteor/versions in test apps.

GitHub CLI patterns for issues, projects, and PRs. Invoke when: creating issues, linking PRs to issues, updating project status, or any GitHub project operations.

When the user wants to plan email marketing, EDM, newsletter strategy, or email deliverability. Also use when the user mentions "email marketing," "EDM," "newsletter," "SPF," "DKIM," "DMARC," "email deliverability," "email content strategy," "email campaigns," "newsletter strategy," "email automation," or "cold email." For signup UI, use newsletter-signup-generator.

Receive and verify Shopify webhooks. Use when setting up Shopify webhook handlers, debugging signature verification, or handling store events like orders/create, products/update, or customers/create.

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.

Databricks SQL (DBSQL) advanced features and SQL warehouse capabilities. This skill MUST be invoked when the user mentions: "DBSQL", "Databricks SQL", "SQL warehouse", "SQL scripting", "stored procedure", "CALL procedure", "materialized view", "CREATE MATERIALIZED VIEW", "pipe syntax", "|>", "geospatial", "H3", "ST_", "spatial SQL", "collation", "COLLATE", "ai_query", "ai_classify", "ai_extract", "ai_gen", "AI function", "http_request", "remote_query", "read_files", "Lakehouse Federation", "recursive CTE", "WITH RECURSIVE", "multi-statement transaction", "temp table", "temporary view", "pipe operator". SHOULD also invoke when the user asks about SQL best practices, data modeling patterns, or advanced SQL features on Databricks.

Databricks CLI operations and the parent/entry-point skill for Databricks CLI use: authentication, profile selection, and bundles. Load this first for CLI, auth, profile, and bundle tasks, then load the matching product skill. For finding or exploring data, answering questions about the data, or generating SQL, load the databricks-data-discovery skill (it routes to Genie One). Contains up-to-date guidelines for Databricks-related CLI tasks.

Use for AI strategy decisions: API vs fine-tune vs build, EU AI Act or US state risk classification, when self-hosting pays off, or AI hiring order. Runs model_buildvsbuy_calculator.py, ai_risk_classifier.py and ai_cost_economics.py.

Curate what the agent has learned into durable project knowledge. Reviews Claude Code auto-memory (MEMORY.md and its topic files) for learnings worth keeping, promotes proven ones into CLAUDE.md or .claude/rules/, records a correction as a lesson that persists across sessions, prunes stale or duplicate entries, and turns a recurring fix into a reusable skill. Use whenever the user asks what you have learned or saved about the project, which memories should become permanent rules, to remember a lesson or stop repeating a mistake, or to clean up, audit or check memory health.

Legal review of contracts and term sheets (MSA, SaaS, NDA, DPA, employment), IP strategy and regulatory exposure (HIPAA, GDPR, FDA, fintech). Use whenever the user asks if a contract is risky or what to watch in a deal; not a substitute for licensed counsel.

CTO decisions: tech debt, architecture direction, scaling the engineering team, technology evaluation, DORA metrics. Use whenever the user asks whether to rewrite, how to grow the eng team or which tech to bet on.

Use for data strategy decisions: training models on customer data, warehouse vs lakehouse vs mesh, valuing data for a raise or M&A, or data hiring order. Runs ai_training_data_audit.py, data_product_strategy_picker.py and data_asset_valuator.py.

Use for retention strategy, customer segmentation or CS team sizing decisions (GRR vs NRR, churn causes, pooled vs named CSMs). Runs retention_decomposition_analyzer.py, customer_segmentation_designer.py and cs_coverage_calculator.py.

Use when assessing an AI/ML system or LLM agent for prompt injection, jailbreaks, model inversion, data poisoning or tool abuse. Maps findings to MITRE ATLAS and scores robustness with ai_threat_scanner.py.

Use when building a bookings, ARR, pipeline or NRR forecast, or a commit, best-case and pipeline board number. Forecasts with bookings_forecaster.py, projects cohorts with cohort_arr_projector.py and scores stage confidence with funnel_confidence_scorer.py, showing every conversion assumption.

Use when the user wants their inbox processed ('triage my inbox', 'check my email'). Classifies recent mail with the inbox-setup knowledge base, drafts replies it never sends (checked by draft_safety_validator.py) and reports.

Use when content should be cited by ChatGPT, Perplexity, Claude or Gemini (answer engine optimization), before rewriting it. Scores E-E-A-T and structure with aeo_audit.py, rewrites with aeo_optimizer.py and logs citations with citation_tracker.py.

Use when deciding what content to create (topics, clusters, a blog or content plan), before listing ideas. Maps topic clusters with topic_cluster_mapper.py and ties each piece to a funnel stage and search demand.

Router for project-management skills: sprints, portfolio health, Jira, Confluence, stakeholder comms, plus a delivery loop. Use whenever a delivery request is unclear about which PM skill fits, or the user asks to run a delivery loop or pull Jira data into one.

Build a LinkedIn plan rather than a post: content pillars, positioning, a sustainable cadence, whether to start a newsletter. Use whenever the user asks what to post about, how often, or how to grow.