note-taking

Note-Taking

This skill enables an AI agent to manage a complete note-taking workflow: creating structured notes, appending to existing ones, organizing notes with tags and categories, searching and retrieving notes by topic, and synthesizing notes into summaries. Notes are stored as Markdown files in a configurable directory, following naming conventions that enable easy browsing and retrieval. The skill supports various note types including meeting notes, daily logs, research notes, idea capture, and project documentation.

Workflow

1. Determine the Note Type and Structure: Based on the user's request, identify the appropriate note type — meeting notes, idea capture, research notes, daily log, or project notes. Each type has a recommended template with relevant sections (e.g., meeting notes include attendees, agenda, discussion, action items; research notes include source, key findings, questions).

2. Create or Locate the Note: Check if a relevant note already exists by searching the notes directory by filename and content. If the user wants to add to an existing topic, open and append to that note. If it is a new topic, create a new file with a descriptive, date-prefixed filename (e.g., 2026-02-12-sprint-planning.md).

3. Write Structured Content: Format the note content using clear Markdown: headings for sections, bullet points for lists, checkboxes for action items, and bold text for key terms. Include metadata at the top (date, tags, related notes) to enable future retrieval.

4. Organize with Tags and Links: Add tags to the note's metadata to enable filtering by topic, project, or type. Where relevant, add links to related notes to build a connected knowledge base.

5. Retrieve and Synthesize: When the user asks for information, search notes by filename, tags, or content. For broad queries ("What did we discuss about authentication this month?"), synthesize relevant notes into a summary rather than returning raw file contents.

Usage