Claude Code Wsl Setup

Feature comparison matrix across competing products and prior art

Design component interaction specs with all visual states, transitions, and accessibility requirements

Evaluate and design data warehouse schemas — star, snowflake, data vault, OBT — with grain definition, SCD strategies, and normalization trade-offs

Changelog entries and migration guides for breaking changes with version strategy

Audit logging design with event catalogs, log schemas, and retention policies

Telemetry events, A/B test instrumentation, and success metrics design

Data sensitivity classification with handling requirements per tier

Mobile navigation patterns, deep linking, and state preservation

RICE scoring framework for evidence-based feature prioritization

Documentation architecture with audience mapping, onboarding paths, and maintenance schedules

Monitoring, alerting, and logging strategy with SLI/SLO definitions

Hardware API integration — sensors, permissions, biometrics

Systematic edge case discovery using structured enumeration techniques

Systematic failure scenario discovery and resilience mitigations

Use when reviewing physical implementation security for power domain coupling, timing-related leakage, clock domain crossing issues, and layout-level information exposure. Covers DPA/SPA resistance, EM emanation, fault injection countermeasures, and probing defenses. Do not use for RTL logic review (use rtl-security-review) or microarchitectural attack analysis (use microarch-analysis).

Firmware design patterns, RTOS selection, memory and power management

Use this skill when scoping a new consulting engagement — "help me scope this project," "I need an engagement brief," or gathering client context through conversational clarification. Transforms natural-language descriptions into structured engagement briefs with targeted questions, sensitivity inference, and stakeholder mapping. Do NOT use for technology research (research-skill), risk assessment (assessment-skill), or client-facing deliverables (deliverable-skill).

Use this skill when conducting structured technology research — "research these vendors," "do a landscape scan," "compare these technologies," or gathering evidence for consulting engagements. Performs source-orchestrated research with landscape scans, candidate profiling, evidence gathering, and comparative analysis producing findings for downstream assessment. Do NOT use for risk scoring (assessment-skill), engagement scoping (intake-skill), or client deliverables (deliverable-skill).

Token hierarchy, theming strategy, and cross-platform consistency

Use this skill when connecting AI or LLMs to data platforms. Covers MCP servers for warehouses, natural-language-to-SQL, embeddings for data discovery, LLM-powered enrichment, and AI agent data access patterns. Common phrases: "text-to-SQL", "MCP server for Snowflake", "LLM data enrichment", "AI agent access". Do NOT use for general data integration (use data-integration) or dbt modeling (use dbt-transforms).

Use this skill when writing Python code for data pipelines or transformations. Covers Polars, Pandas, PySpark DataFrames, dbt Python models, API extraction scripts, and data validation with Pydantic or Pandera. Common phrases: "Polars vs Pandas", "PySpark DataFrame", "validate this data", "Python extraction script". Do NOT use for SQL-based dbt models (use dbt-transforms) or integration architecture (use data-integration).