Skill UI

This comprehensive guide provides step-by-step instructions to optimize localization spending on Lokalise. Learn how to audit current usage across projects and languages, minimize per-seat costs by managing contributor access, maximize Translation Memory (TM) hits, and efficiently triage Machine Translation (MT) to keep your localization projects well within budget.

This advanced engine acts as the memory layer for C-suite advisory sessions. It loads, manages, and enriches detailed company context from local files, automatically detecting context staleness. Crucially, it enforces strict anonymization protocols before any external API calls, ensuring sensitive data (like revenue or names) is protected while providing deep, specific insights for high-level business strategy.

A two-layer memory architecture designed for managing corporate board meeting decisions. It separates raw, unfiltered transcripts (Layer 1) from founder-approved, canonical decisions and action items (Layer 2). This system ensures historical accuracy, tracks overdue tasks via commands like /cs:review, and actively detects topic contradictions and conflicts to maintain governance integrity.

This tool serves as the formal gate for documenting corporate decisions made during high-level meetings, such as boardrooms. It logs the founder's final, approved memo, creating a durable, structured record that feeds into future planning cycles. It maintains a two-layer memory system: raw transcripts for reference, and approved decisions for actionable, official company memory, ensuring accountability and historical continuity.

This meta-skill provides an auditable workflow for professional compliance self-assessments (e.g., GDPR, SOC2). It executes deep research while retaining citation evidence, then compiles the findings into a comprehensive package: a signable DOCX report, a read-only PDF archive for permanence, and a persistent memory note to guarantee the evidence chain is recallable. Ideal for structured policy auditing.