Analyze a book (EPUB/PDF) and generate detailed chapter-by-chapter notes with extracted key concepts. Use when given a book file path to process.
日本語の概要は準備中です。原文の説明を表示しています。
Deep cross-domain synthesis engine for the vault. Triggers on "synthesize X", "what do I know about X", "connect ideas about X", "cross-domain analysis of X", "map everything in the vault about X". Searches comprehensively, surfaces non-obvious patterns and tensions, then challenges the user to generate original thought. The vault should surprise you — if synthesis only confirms what you already think, it failed.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Science grounding: far transfer (Tempel & Frings 2024), generation effect (McCurdy et al. 2020), elaborative interrogation, desirable difficulty (Bjork & Bjork 2020). </Purpose>
<Use_When>
<Do_Not_Use_When>
Extract the core concept(s) from the user's input. Identify:
If the topic is ambiguous, briefly clarify before searching (one question max).
MCP search (preferred):
search_notes(query="PRIMARY TERM", limit=30)
search_notes(query="SYNONYM 1", limit=15)
search_notes(query="SYNONYM 2", limit=15)
Grep fallback (if MCP unavailable):
Grep(pattern="PRIMARY TERM", path="notes/", glob="*.md", output_mode="files_with_matches")
Grep(pattern="#TAG-NAME", path="notes/", glob="*.md", output_mode="files_with_matches")
Grep(pattern="\[\[.*PRIMARY TERM.*\]\]", path="notes/", glob="*.md", output_mode="files_with_matches")
Also search:
Grep(pattern="PRIMARY TERM", path="notes/thoughts/", glob="*.md")Grep(pattern="type: term", path="notes/", glob="*.md") then filterCollect all matching file paths. Deduplicate. Aim for 15–25 notes across diverse domains.
Read up to 20 most relevant notes using read_multiple_notes or individual read_note calls.
Prioritize:
While reading, track:
Output this structure (adapt headings as needed, cut any section with nothing real to say):
[3–6 bullets. Each = one non-obvious claim distilled from multiple notes. Lead with the sharpest insight. No filler.]
[Table or bullet list: Domain → how the concept appears there. Include only non-obvious mappings — skip domains where the concept is trivially expected.]
| Domain | How [topic] appears |
|---|---|
| [domain] | [specific claim from that note] |
[What multiple notes converge on — the vault's "consensus". 2–4 bullets max.]
[Where notes disagree — including tensions the user may not have noticed. THIS IS THE MOST VALUABLE SECTION. If two notes from different domains make opposing claims, surface it explicitly. Quote the note titles.]
[What's missing: questions the vault raises but doesn't answer, adjacent concepts not yet captured, domains that probably have something to say but no notes exist]
Ask 3–4 questions. Make them uncomfortable. Reference the user's OWN notes by name.
Rules for good challenge questions:
Wait for user responses before proceeding to Stage 6.
The vault should not just confirm what you know. If the synthesis has no tension and no surprises, say so explicitly: "I found strong consensus but no real tension — either the topic is genuinely settled, or the vault has a blind spot here."
Help the user create a Thought note. Do NOT write it for them — Thoughts are where human understanding lives. Instead:
Thought note template:
---
id: YYYYMMDDHHMMSS
created_date: YYYY-MM-DD
updated_date: YYYY-MM-DD
type: thought
processing_status: processed
---
# (Thought) [Title]
- **🏷️Tags** : #thought #[topic-tag] #MM-YYYY
[ ](#anki-card)
## Notes
[User fills this]
## Links
- [[(Type) Source Note 1]]
- [[(Type) Source Note 2]]
Only propose this if the concept appeared across multiple notes but has no dedicated Term note. Create the Term note with:
---
id: YYYYMMDDHHMMSS
created_date: YYYY-MM-DD
updated_date: YYYY-MM-DD
type: term
processing_status: processed
---
# (Term) [Concept Name]
- **🏷️Tags** : #term #all-anki #[topic-tag] #MM-YYYY
[ ](#anki-card)
## Notes
[Distilled definition — Feynman-style: intuition first, formalism second]
- [Key insight 1]
- [Key insight 2]
- **Example**: [concrete example]
- **Cross-domain**: [where else this appears]
## Links
- [[(Type) Source 1]]
Every internal reference must use the full filename stem including (Type) prefix:
[[(Thought) My insight note]][[My insight note]]If unsure of the exact filename, search before linking.
</Steps> <Examples> <Good> User: "synthesize everything about attention mechanisms" → Search returns: 3 ML papers on attention, 1 psychology note on selective attention, 1 design note on visual hierarchy, 1 thought note on "attention as resource allocation" → Cross-domain: ML attention ≠ psychological attention — but both involve a scoring function that weights inputs. Surface this non-obvious parallel. → Tension: vault's ML notes say "attention is O(n²)" (a problem), but the thought note says "the bottleneck IS the feature" — unresolved. → Challenge: "Your [[(Thought) Attention as resource allocation]] treats attention as scarce. But transformers have unlimited heads. Does scarcity still apply? What breaks?" </Good> <Good> User: "what do I know about loss aversion" → Search finds notes in: psychology, behavioral economics, startup, design (dark patterns) → Agreements: loss aversion is asymmetric (losses hurt ~2x more than gains) → Gap: no notes on whether loss aversion weakens with experience/expertise — ask if worth capturing → Challenge: "You have [[(Paper) Prospect Theory]] and [[(Post) Pricing psychology]]. Your startup notes apply this to pricing, but never to hiring. Where else in the vault could loss aversion explain something you attributed to something else?" </Good> <Bad> User: "synthesize ML" → Too broad — ask: "ML is too wide to synthesize well. What angle? Scaling, optimization, architectures, learning theory, RL...?" </Bad> <Bad> Synthesis that produces no tension: → "Everything agrees that attention is useful." — This is not synthesis. Push harder: find the domains that don't agree, find the edge cases, find what the vault hasn't said. </Bad> </Examples><Escalation_And_Stop_Conditions>
$ARGUMENTS
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Analyze a book (EPUB/PDF) and generate detailed chapter-by-chapter notes with extracted key concepts. Use when given a book file path to process.
日本語の概要は準備中です。原文の説明を表示しています。
Process an online course into detailed vault notes — one per lecture, with slides and transcripts synthesized. Use this skill whenever the user shares a course URL, syllabus page, or lecture playlist and wants structured notes from it. Also triggers on "process this course", "take notes on these lectures", "course notes", any university course page, or when someone pastes a link to a course with multiple lectures/sessions. Even if the user just says "check out this course" or drops a .edu link with a schedule — use this skill.
日本語の概要は準備中です。原文の説明を表示しています。
Deep, iterative, multi-source research that explores a topic from multiple perspectives, detects contradictions, and produces a comprehensive vault note with fact-level citations and a confidence map. Use this skill whenever the user says /deep-research, "deep research X", "research X thoroughly", "investigate X deeply", "I need to really understand X", or wants research that goes beyond a quick web search. Also use when the user wants to understand a complex, contested, or multi-faceted topic, compare competing approaches with evidence, or build a comprehensive mental model they can trust for decisions. This is heavier than /research — it searches web, academic papers, Reddit, and the vault, then loops through exploration and critique rounds until the evidence base is solid. When in doubt between /research and /deep-research, prefer this one if the topic is complex, contested, or the user wants depth over speed.
日本語の概要は準備中です。原文の説明を表示しています。
Initialize an Obsidian vault with the agent-ready Zettelkasten system — creates directory structure, templates, CLAUDE.md, MCP config, and hooks
日本語の概要は準備中です。原文の説明を表示しています。
Extract transcript and key slides from a local video file, then create a vault-formatted lecture note. Use this skill whenever a user provides a local video file (.mp4, .mov, .mkv, .avi, .webm) and wants notes from it. Triggers on "lecture", "take notes", "I have a recording of", "class video", "transcribe this presentation", "process this video for notes", or /lecture. Works with any language — auto-detects transcript language.
日本語の概要は準備中です。原文の説明を表示しています。
Use when searching for academic papers related to a topic, finding papers similar to one already in the vault, or discovering research gaps. Triggers on "find papers", "related papers", "paper search", "literature", "what papers should I read about X".
日本語の概要は準備中です。原文の説明を表示しています。