Use when preparing data for machine learning from SQL Server — feature engineering in T-SQL, building training/test datasets, statistical aggregations for ML pipelines, sampling strategies, data normalization and encoding in SQL, writing queries that feed pandas or scikit-learn, exporting to Parquet or CSV for model training, or when a data scientist asks for a 'feature table' or 'training set' from a SQL Server database.

Use when writing T-SQL for business intelligence, analytics, or reporting. Includes building summary reports with GROUPING SETS, ROLLUP, and CUBE, writing time-series queries with date bucketing, creating pivot/unpivot transformations, generating tally/numbers tables for gap-filling, building running totals and moving averages with window functions, writing year-over-year comparisons, designing materialized views for dashboards, or producing CSV/JSON exports from SQL Server.

Writes, optimizes, and debugs T-SQL queries. Explains SQL Server internals, troubleshoots performance issues, and guides database administration tasks including backup/restore, high availability, security, and index design. Use when the user asks about T-SQL syntax, SQL Server administration, query performance, stored procedures, indexes, locking, transactions, backup/restore, high availability, security, or any MSSQL-related topic — even without saying 'SQL Server' explicitly. Also trigger on terms like SSMS, tempdb, bcp, sqlcmd, MSSQL, sp_executesql, NOLOCK, columnstore, Hekaton, RCSI, param sniffing, or execution plan.

Implements and enforces full DDD (domain-driven design) conventions for TypeScript/Next.js projects using functional patterns. Validates folder structure against DDD layers, enforces dependency rules between domain/application/infrastructure layers, generates domain module scaffolding, and reviews code for bounded context violations. Use when the user asks about domain-driven design, project architecture, bounded contexts, layer separation, clean architecture, hexagonal architecture, ports and adapters, or organising a TypeScript/Next.js codebase with a domain model, aggregate, value object, or ubiquitous language.

Draft Statements of Work (SOWs) from client templates and Metis proposals, and review/redline Master Services Agreements (MSAs) from the Supplier perspective. Use whenever a consultant asks to draft an SOW, populate a client SOW template, review contract terms, redline an MSA, do a risk analysis, or check for scope creep. Trigger on "SOW," "MSA," "master agreement," "statement of work," "redline," "contract review," deliverable tables, invoice schedules, or IP carve-outs. This skill produces text and legal analysis, not formatted documents. Do NOT use for: client proposals (metis-premier-proposal); branded PDF documents (metis-pdf-creator); presentations (metis-pptx).

Turn rough ideas into clear work orders before planning or building. Use when request is vague like "add a button", "make it better", "fix the thing". Triggers on ambiguous or underspecified requests. Produces a brief with scope, acceptance criteria, and stop conditions.

Launch Chrome with an unpacked extension and test its UI via CDP. Auto-installs Chrome for Testing if needed. Loads the extension, opens sidepanel/popup/options page, and hands off to cdp-connect for interaction (click, type, screenshot, ax-tree). Handles Chrome 137+ branded build restrictions (Extensions.loadUnpacked via pipe), sidepanel user gesture requirements, and React input quirks. Use when you need to test a Chrome extension's UI, automate extension interactions, or validate extension behavior on a target page. Triggers on: chrome extension test, test extension, load unpacked extension, extension sidepanel, extension popup, test chrome extension, extension testing, chrome extension automation, ext pilot, cdp extension.

Search for Israel Rail train schedules using the railil CLI. Use when the user asks about Israeli trains, Israel Rail schedules, train routes in Israel, or mentions the railil tool. Find routes between stations with fuzzy search, filter by date/time, and output in various formats (JSON, Markdown, Table).

Prepare any webpage for clean interaction by detecting and removing disruptive overlays (cookie banners, GDPR consent, modals, popups, newsletter signups, paywalls, login walls). Uses a cached database of 300+ known CMPs (Consent-O-Matic + EasyList) combined with heuristic DOM scanning. Produces portable JS recipes for any browser tool (Playwright, CDP, cmux-browser). ALWAYS use this skill before taking screenshots, scraping content, or automating interaction on any webpage that might have overlays blocking the view or preventing interaction. Triggers on: page prep, clean page, remove overlays, dismiss cookie banner, page blocked, overlay cleanup, consent banner, prepare page, unblock page, clear popups, cookie popup.

Teleport a Kite task session to local Claude Code. Takes a teleport token generated by /kite teleport in Slack, fetches the converted session from the Kite worker, places it in the Claude Code session directory, and offers branch checkout. Use when: resuming a Kite task locally, teleporting a remote session, continuing cloud work in Claude Code. Triggers on: kite teleport, teleport session, resume kite task, kite token, kt_.

Metis Strategy brand identity reference and compliance layer. Automatically consulted by metis-pptx, metis-html-slides, metis-pdf-creator, metis-whitepaper, and metis-premier-proposal during output generation. Also use standalone when the user asks about "Metis colors," "our brand," "on-brand," "Metis template," "client-facing" standards, or wants a brand compliance review of existing output. Covers color palette, typography, logo usage, graphic devices, photography treatment, and editorial voice. Do NOT use for creating documents or deliverables directly; use the appropriate output skill (metis-pptx, metis-pdf-creator, etc.) instead. When in doubt, apply the brand.

Runs the final validation phase of a project plan by executing the full test suite, lint and format checks, removing temporary scaffolding, and writing a structured validation report with command outputs and success-criteria evidence to `context/plans/{plan_name}.md`. Use when the user wants to verify a completed implementation, confirm all success criteria are met, wrap up a plan, finalize a feature or fix, or sign off on a change before closing it out.

Creates a structured handover document summarizing task context, decisions made, open questions, and recommended next steps — saved to `context/handovers/`. Use when a user wants to hand off, transition, or pass a task to someone else, create handover notes, write a task transition document, or capture current progress for a future session. Trigger phrases include "create a handover", "hand this off", "write handover notes", "pass this task on", or "document where I'm up to".

Runs the final validation phase of a project plan by executing the full test suite, lint and format checks, removing temporary scaffolding, and writing a structured validation report with command outputs and success-criteria evidence to `context/plans/{plan_name}.md`. Use when the user wants to verify a completed implementation, confirm all success criteria are met, wrap up a plan, finalize a feature or fix, or sign off on a change before closing it out.

Creates a structured handover document summarizing task context, decisions made, open questions, and recommended next steps — saved to `context/handovers/`. Use when a user wants to hand off, transition, or pass a task to someone else, create handover notes, write a task transition document, or capture current progress for a future session. Trigger phrases include "create a handover", "hand this off", "write handover notes", "pass this task on", or "document where I'm up to".

Use when the user wants to fix stale or outdated context documentation that no longer matches the actual codebase — e.g. "update docs", "sync context files", "fix outdated documentation", "refresh context", or "context is out of date". Audits files in `context/`, identifies discrepancies between documentation and implemented code (treating code as the source of truth), then updates context files to remove outdated references, correct stale descriptions, and sync documentation with recent code changes.

Creates the SCE (Shared Context Engineering) baseline `context/` directory structure — a set of markdown files and sub-folders used as shared project memory (overview, architecture, patterns, glossary, decisions, plans, handovers, and a temporary scratch space). Use when the `context/` folder is missing from the repository, when a user asks to initialise the project context, set up context, create baseline documentation structure, or when shared configuration files for project memory are absent.

Use when the user wants to fix stale or outdated context documentation that no longer matches the actual codebase — e.g. "update docs", "sync context files", "fix outdated documentation", "refresh context", or "context is out of date". Audits files in `context/`, identifies discrepancies between documentation and implemented code (treating code as the source of truth), then updates context files to remove outdated references, correct stale descriptions, and sync documentation with recent code changes.

Creates the SCE (Shared Context Engineering) baseline `context/` directory structure — a set of markdown files and sub-folders used as shared project memory (overview, architecture, patterns, glossary, decisions, plans, handovers, and a temporary scratch space). Use when the `context/` folder is missing from the repository, when a user asks to initialise the project context, set up context, create baseline documentation structure, or when shared configuration files for project memory are absent.

Use when working with Schema Registry for Apache Kafka, Confluent Platform, or Confluent Cloud. Covers schema management (Avro, Protobuf, JSON Schema), compatibility modes, schema evolution, REST API, serializer/deserializer configuration, Kafka Connect converters, and Flink SQL integration with Schema Registry. Trigger this skill whenever the user mentions schema registry, schema evolution, Avro/Protobuf/JSON Schema serialization with Kafka, subject naming strategies, compatibility checking, or Flink SQL with Confluent formats (avro-confluent). Also trigger when users ask about data contracts, schema validation, or serializer/deserializer configuration for Kafka producers and consumers.