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My second brain

Skill siqiyaoyao/my-second-brain/skill/my-second-brain

A reusable Agent Skill for turning a personal knowledge vault into a source-preserving capture-to-output system.

Install
npx -y skills add siqiyaoyao/my-second-brain --skill my-second-brain

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  • 14 days oldThe repository was created 14 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
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What its author says it does

Copied from the file, not written here

Build, maintain, and process a personal knowledge vault with a source-preserving workflow: capture inbox/source material, triage it into Sources/Notes/Projects/Outputs, compile sources into knowledge cards or method cards, preserve citations, leave My Take and Open Questions, update MOCs/projects/outputs, refresh Dashboard.md, and write handoff notes. Use when the user asks to process collected notes, organize an Obsidian vault, create or update a second brain, turn articles/chats/projects into reusable knowledge, inspect vault health, generate outputs from notes, or save something from the current conversation into their knowledge vault — e.g. 'save this insight/decision/discussion to my brain / second brain / knowledge vault', '收进 brain', '存进知识库', 'remember this in my vault'. Supports English, Chinese, or the vault's existing language.

SKILL.md

7.6 KB, ~1.6k tokens by cl100k_base, as published. Nobody here has run it

My Second Brain

Use this skill to help a user operate a personal knowledge vault as a living system, not a dumping ground. The core loop is:

Capture -> Triage -> Compile -> Connect -> Projectize -> Publish -> Review

Defaults

  • Target folder: current working directory unless the user provides a path.
  • Language: follow the user's language. If unclear, use the vault's existing language.
  • Preserve user-written content. Prefer appending update sections or new linked notes over overwriting.
  • Do not move application code into the vault. Store knowledge and path pointers only.
  • Treat original sources as raw evidence: preserve source links, mark uncertainty, and avoid inventing facts.
  • My Take belongs to the user. You may draft suggestions, but clearly label them if they are AI-proposed.

First Read

For an existing vault, read these if present:

  1. AGENTS.md
  2. HANDOFF.md
  3. _System/AGENTS.md
  4. _System/Workflows.md
  5. _System/Schema.md
  6. Dashboard.md

For a folder that is not yet a vault, read references/vault-method.md and references/schema.md, then create the smallest useful structure.

Decision Tree

User wants to process newly collected material

  1. Inspect 0 Inbox/, 1 Sources/, and any files the user named.
  2. Triage each item:
    • Raw article, transcript, clipping, chat log -> 1 Sources/
    • Reusable concept -> 2 Notes/ with type: note
    • Repeatable procedure -> 2 Notes/ with type: method
    • Active work or experiment -> 3 Projects/ with type: project
    • Public-facing draft -> 5 Outputs/ with type: output
  3. Compile valuable sources into concise notes. Keep citations and uncertainty.
  4. Add My Take and Open Questions sections where useful.
  5. Update related MOCs or create one when a topic has enough notes.
  6. Refresh Dashboard.md.
  7. Tell the user the 1-3 human decisions or My Takes they should supply.

Read references/workflows.md before doing multi-file processing.

User wants a clear after-collection checklist

Give the minimal executable checklist in the user's language:

  1. Triage new 0 Inbox and 1 Sources content.
  2. Decide what to archive and what to compile.
  3. Turn valuable material into 2 Notes knowledge cards or method cards.
  4. Preserve sources and mark uncertainty.
  5. Leave My Take and Open Questions.
  6. Create or update 3 Projects when knowledge needs action.
  7. Create 5 Outputs drafts when knowledge can be published.
  8. Refresh Dashboard.md.
  9. End with the top 1-3 human decisions.

User wants to initialize a vault

  1. Create only the minimal folders: 0 Inbox, 1 Sources, 2 Notes, 3 Projects, 4 Me, 5 Outputs, _System, Attachments.
  2. Create or merge _System/Schema.md, _System/Workflows.md, AGENTS.md, HANDOFF.md.
  3. Copy or adapt templates from assets/.
  4. Add lightweight scripts only if the user wants automation.
  5. Do not create large empty taxonomies.

Read references/schema.md and references/vault-method.md.

User wants a vault health check

  1. Run local vault scripts if they exist:
    • python scripts/dashboard.py --save
    • python scripts/notes_status.py
    • python scripts/vault_report.py
  2. If the vault lacks these scripts, use bundled scripts from this skill with --vault <target>.
  3. Summarize:
    • uncompiled sources
    • notes missing My Take
    • unanswered Open Questions
    • draft outputs
    • stuck projects
  4. Recommend one next action, not ten.

Read references/dashboard-rules.md.

User wants to save something from the current conversation

This is live capture, not file processing. Keep friction near zero:

  1. Distill what the user pointed at (an insight, decision, method, gotcha, or the whole discussion) into a concise note. Do not dump the raw transcript.
  2. Route by nature, defaulting to lightweight:
    • Not sure where it belongs -> a seed note in 0 Inbox/ (one file, frontmatter + a few lines). Never block capture on classification.
    • Clear reusable concept/insight -> 2 Notes/ (type: note)
    • Repeatable procedure -> 2 Notes/ (type: method)
    • Belongs to an existing project -> append to that project card's log/decisions instead of a new file.
  3. Set source: to something like conversation <YYYY-MM-DD> (<topic or tool>) so provenance survives.
  4. The user's own words go in My Take; anything you inferred is labeled AI-proposed. Add 1-2 [[links]] to related notes if obvious.
  5. Confirm in one line what was saved and where. Skip dashboard refresh unless asked — quick capture should feel instant.

User wants to turn knowledge into output

  1. Gather the relevant notes/projects.
  2. Identify the user-owned angle, not just facts.
  3. Draft into 5 Outputs/.
  4. Mark sections needing user confirmation.
  5. Link the output back to source notes and projects.

Bundled Resources

  • references/vault-method.md: mental model, principles, and when to split vaults.
  • references/schema.md: recommended frontmatter and folder conventions.
  • references/workflows.md: capture-to-output SOPs and common user prompts.
  • references/dashboard-rules.md: dashboard and participation checks.
  • assets/Source.md, assets/Note.md, assets/Method.md, assets/Project.md, assets/Output.md: starter templates.
  • scripts/new.py, scripts/dashboard.py, scripts/notes_status.py, scripts/vault_report.py: portable standard-library helpers. Run with --vault <target> if not executing from the vault root.

Activation Limits and the Standing Rule

A skill only fires when the user's request matches its description — it cannot watch conversations in the background and decide on its own that something is worth saving. To close that gap, offer to install a short standing rule in the user's global agent config (~/.claude/CLAUDE.md for Claude Code, ~/.codex/AGENTS.md for Codex), adapted to their language:

## Knowledge Capture
- I keep a personal knowledge vault at <vault path> (skill: my-second-brain).
- When a session produces durable value (an insight, method, decision, or hard-won gotcha),
  proactively ask once: "Want me to save X to your vault?" If yes, use my-second-brain.
- Test: still useful in a month, or in another project? If not, don't ask.
- If I say "save this to my brain" (or equivalent), just do it.

Offer this during vault initialization, and whenever a user wonders why insights aren't being captured automatically. This is advisory (not guaranteed); for a hard guarantee suggest a SessionEnd hook, noting it fires every session and can feel naggy.

Finish Every Session

Before finishing, update HANDOFF.md if present, refresh Dashboard.md when content changed, and report:

  • files created/updated
  • what was compiled or linked
  • what the user needs to decide or write next

Gives 0 of the 12 instructions most note taking skills give in ~1.6k tokens

Counted across 686 of the 876 authors here whose files we hold, read 2026-08-07

  • include a visual element on every slidein 44 of 686, across 13 files
  • use wikilinks for internal vault linksin 36 of 686, across 12 files
  • commit to a single visual motif across every slidein 34 of 686, across 9 files
  • use subagents to visually inspect rendered slidesin 31 of 686, across 7 files
  • read pptxgenjs guide before creating presentations from scratchin 30 of 686, across 6 files
  • keep 0.5 inch minimum marginsin 30 of 686, across 7 files
  • re-verify affected slides after every fixin 27 of 686, across 5 files
  • run content QA checks before declaring successin 26 of 686, across 3 files
  • Use Markdown links for external URLs onlyin 26 of 686, across 11 files
  • pick a bold topic specific color palettein 24 of 686, across 2 files
  • read editing guide before editing existing presentationsin 23 of 686, across 1 file
  • use one dominant color across all slidesin 23 of 686, across 1 file

Said here and by no other author read

  • preserve user-written content over overwriting
  • append new sections rather than overwriting files
  • store knowledge and path pointers only
  • label AI-proposed suggestions clearly
  • triage inbox items by type into designated folders
  • compile valuable sources into concise notes

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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