AgentSkillsCN

summarize-note

利用 Ollama 为 Markdown 笔记生成 AI 摘要，并填充 frontmatter 中的 `summary` 属性。对于超出模型上下文范围的笔记，采用分层 Map-Reduce 方法进行处理。当您被要求对笔记进行摘要总结、生成笔记概要、将 AI 摘要添加至 frontmatter，或批量汇总 Obsidian 知识库中的笔记时，可触发此技能。

SKILL.md
--- frontmatter
name: summarize-note
description: >
  Generate AI summaries for markdown notes using Ollama and populate the
  frontmatter `summary` property. Use hierarchical map-reduce for notes
  exceeding model context. Trigger when asked to summarize notes, generate
  note abstracts, add AI summaries to frontmatter, or batch-summarize
  Obsidian vault notes.
allowed-tools: Read, Grep, Glob, Bash

Instructions

  1. •

    Ask the user which Ollama model to use (e.g., qwen3:8b, llama3, gemma2). The model must already be pulled in Ollama.

  2. •

    Dry-run first to preview summaries without modifying files:

    bash
    uv run --with ollama,pyyaml \
    skills/summarize-note/scripts/summarize_note.py <model> --dry-run <file_path> [...]
  3. •

    If summaries look good, run without --dry-run to write them:

    bash
    uv run --with ollama,pyyaml \
    skills/summarize-note/scripts/summarize_note.py <model> <file_path> [...]
  4. •

    Review the JSON output to confirm summaries were generated and written correctly.

Key behaviors

  • •Notes with an existing human summary (no [AI] prefix) are skipped automatically.
  • •Long notes are split by headings and summarized via concurrent map-reduce.
  • •Thinking model tags (e.g. <think>) are stripped automatically.
  • •Use --chunk-size to adjust for models with smaller context windows (default: 50000 chars, ~12K tokens, sized for 32K+ context models).
  • •Use --base-url to point to a remote Ollama instance.