skills/obsidian-batch-yaml/SKILL.md
Autonomously scans specific directories (00, 10, 20, 30) in an Obsidian vault, analyzes note content, and intelligently merges AI-generated YAML frontmatter (tags, summary, aliases) into the notes.
npx skillsauth add jaimeparker/stable-jarvis obsidian-batch-yamlInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill automates the process of enhancing your Obsidian "Cyber Brain" by adding structured, AI-suitable YAML frontmatter to existing Markdown notes. It is designed to run autonomously across your most active research and project folders.
Trigger: Use when the user wants to "standardize", "process", or "add metadata/tags/summaries" to existing notes in the 00, 10, 20, or 30 directories.
Input: Obsidian vault directories 00, 10, 20, and 30.
Output: Updated Markdown notes with merged YAML frontmatter including tags, summary, and aliases.
Follow this iterative, batch-based process to execute the skill.
["00 Inbox/Research Notes.md", "10 Projects/AI Systems.md", "20 Areas/Machine Learning.md"].md) files within the target directories:
00 Inbox/10 Projects/20 Areas/30 Zettelkasten/For each batch of 5 notes, perform the following steps for every note:
60 System/Tag Taxonomy.md. This file defines the approved tag categories:
reinforcement-learning, robotics, motion-planning, trajectory-optimization, optimal-control, control-systemsoffline-rl, offline-to-online, model-based-rl, world-models, imitation-learning, residual-rl, hierarchical-rl, diffusion-policy, real-world-rl, exploration, fine-tuning, reward-design, value-function, policy-gradientsac, ppo, cql, cal-ql, iql, td-mpc, flow-matching, isaac-lab, px4, rlinf, maniskillaerial-grasping, aerial-manipulation, quadrotor-control, quadrotor-dynamics, ai-lab, fast-perching, agile-flightdiscussion, moc, paper-reading, design-doc, training-diagnostics, implementation-plan, sop, research-philosophymcp_obsidian_read_note to load the full content, including any existing YAML.summary: A concise, 1-2 sentence TL;DR of the core insight.tags: 2-4 highly relevant conceptual tags. Priority rule: always select from the existing taxonomy (L1-L5) first. Only create a new tag if no existing tag captures the concept, and only if the concept applies to at least 2+ notes in the vault. All tags must be lowercase kebab-case (e.g., reinforcement-learning, NOT Reinforcement_Learning or RL). Never create tags from hex color codes, code keywords (e.g., include, define), or numeric values.aliases: 1-3 alternative titles or keywords for easier cross-linking.--- delimiters), extract the existing fields.summary field. If one already exists, replace it only if the existing one is empty or significantly less informative.date, type, source) exactly as they are.Before writing, validate the generated tags:
333, f9f, fff3a3a6)include, file, define, config, common, index)Offline-RL and offline-rl → keep offline-rl).mcp_obsidian_patch_note (if replacing only the top block) or mcp_obsidian_write_note to save the updated note.Users can explicitly declare which notes should be processed by providing:
Single Note: Single Folder:
"Process this folder: Research"
"Add YAML to: 10 Projects"
"Handle all notes in: 20 Areas/ML Systems"
Single Note:
"Process this note: My Research Note.md"
"Add YAML to: 10 Projects/AI Research.md"
Multiple Notes (List Format):
["00 Inbox/Note 1.md", "10 Projects/Note 2.md", "20 Areas/Note 3.md"]
Mixed Format (Folders and Notes):
["Research/Deep Learning", "10 Projects/AI Systems.md", "00 Inbox/Quick Notes.md"]
Declaration Rules:
"Research", "10 Projects/Subdir").md extension (e.g., "10 Projects/Note.md")/.md filesBatch Processing: If a user provides more than 5 items (folders or notes), they will automatically be split into batches of 5 and processed iteratively.
--- delimiter). This skill is strictly for YAML frontmatter enhancement.60 System/Tag Taxonomy.md. Prefer existing taxonomy tags; new tags require justification and must follow kebab-case format.#fff3a3a6), code keywords (e.g., #include), or numeric values. These are parser artifacts, not semantic tags.development
# Mao Semantic Search Search Mao Zedong Selected Works by conceptual meaning using vector embeddings. Builds a local embedding index over all 230 articles across 5 volumes, then performs cosine similarity search at query time. ## When to Use - User asks a thematic/conceptual question about Mao's works ("What did Mao say about guerrilla warfare?") - Keyword search over the .md files is insufficient - User wants to find passages related to a concept without knowing exact terminology - As a pre-
development
Use when a researcher is choosing, framing, refining, or stress-testing a research question, hypothesis, thesis topic, project idea, grant direction, paper angle, or stalled research direction.
research
精读文献。快速泛读请用paper-quick-read。
data-ai
泛读:快速概览Zotero库中的文献,单轮LLM生成摘要级Markdown报告,并上传为Zotero Note。深度精读请用paper-deep-reader。