What problem does it solve? Raw information fetched from Slack, Linear, Notion, or GitHub arrives as unstructured text that is hard for downstream workflows to consume. This Skill organizes that material into a fixed, machine-friendly set of categories so follow-up steps can act on it consistently. ## Core Features & Use Cases - Structured Classification: Sorts input into facts, decisions, assumptions, important links, unresolved questions, next actions, user-pending items, and unclassifiable entries. - Strict Boundaries: Never fetches additional data, never updates Projects, Notes, Linear, or GitHub, and never invents new action items beyond what the input explicitly states. - Fixed Output Format: Produces a stable Markdown template with unchanging headings so downstream workflows can parse results mechanically. - Use Case: After fetching a Slack thread about a release decision, pass the transcript to this Skill to separate confirmed decisions from open questions and pending user responses before updating your project notes. ## Quick Start Use the classify-fetched-materials skill to organize the fetched Slack thread and Linear issue comments into facts, decisions, and next actions.
