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Get Started Free →When you want to capture into, compile, query, lint, or connect your personal Second Brain. Wraps the Karpathy LLM Wiki schema (Obsidian or any markdown vault) — raw/ (unprocessed sources), wiki/ (AI-compiled interlinked topic pages), outputs/ (generated artifacts). Tool-agnostic in design but defaults to a vault at ${SECOND_BRAIN_VAULT:-$HOME/Documents/SecondBrain}/. Six modes — capture (drop something into raw/), compile (process unprocessed raw files into wiki pages, update INDEX.md), query (
.claude/skills/coreyhaines31-second-brain/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 90% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 197% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 104% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 246% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 97% | 0% |
Wraps an existing Second Brain in Obsidian (or any markdown-based vault). The wiki vault's CLAUDE.md is the authoritative schema — the skill orchestrates the operations the user has been doing manually.
Three layers, each with a clear role:
raw/ → wiki/ → outputs/
sources compiled generated
artifactsarticle-, idea-, highlights-, braindump-, note-, resource-, tweet-). Never deleted — source of truth.[[wikilinks]]. INDEX.md at root.Folders to leave alone during wiki ops: Projects/, Daily/, Templates/, Inbox/, Notes/, Tasks.md, Kanban.md, Home.md.
references/vault-config.md for the vault path (default: ${SECOND_BRAIN_VAULT:-$HOME/Documents/SecondBrain}/)<vault>/CLAUDE.md for the authoritative schema. If present, trust it over references/schema.md — the user's vault is the source of truth.<vault>/CLAUDE.md, fall back to references/schema.md.| Invocation | Mode | |---|---| | /sb capture / /second-brain capture / "capture this" / "save this to my brain" | capture | | /sb compile / "compile the wiki" / "process raw notes" | compile | | /sb query <question> / "ask my brain X" / "what does my brain say about Y" | query | | /sb lint / "lint the wiki" / "health check my brain" | lint | | /sb connect / "find connections" / "suggest wikilinks" | connect | | /sb search <term> / "search my notes for X" | search |
Inputs: URL, pasted text, file path, or screenshot.
article-highlights-braindump- or idea-tweet-resource-note-<type>-<kebab-case-topic>.md (e.g., article-andrew-wilkinson-tiny-manual.md). Use the source title or topic — not the URL slug.markdown source: <URL if applicable> captured: YYYY-MM-DD
<vault>/raw/.Don't compile into the wiki here — capture is fast intake. Compilation is a separate, deliberate pass.
The expensive but valuable operation. Process unprocessed raw files into wiki pages.
wiki/*.md for Sources sections; the raw files NOT listed are unprocessed.wiki/INDEX.md.[[wikilinks]] for every related concept## Sources section with a one-line note on what was drawn from itwiki/INDEX.md:- [[Page Name]] — brief descriptionOutput: list of pages created/updated, what merged where, anything held for clarification.
Answer a question using ONLY the wiki/raw corpus. Different from deep-research (which goes external).
wiki/INDEX.md to identify potentially relevant pages[[wikilinks]] 1–2 hops/deep-research to expandoutputs/<YYYY-MM-DD>-<question-slug>.md with:--render pdf or --render html was passed, pipe the output through pandoc using the shared stylesheet. See references/schema.md → "Publishing alternatives" for the commands.Health check the wiki.
Check:
[[wikilinks]] to other pages[[wikilink]] between them (suggest /sb connect)Output: prioritized list. Most important first (broken structure beats stale content).
Find pages that should be linked but aren't.
## Connections sectionsQuick grep across wiki/ + raw/ for a term. Return matching files with a 2-line excerpt around the match. Faster than query when the user knows what page they're looking for.
deep-research — when query finds gaps in the wiki, route to deep-research to expand from external sources. Deep-research output can be captured back into raw/ for future compilation.paste — capture content cleanly into raw/ (especially for terminal/CLI captures).business-brainstorm — checks Portfolio of Businesses and Entrepreneurship & Startups wiki pages for relevant context before brainstorming.decide — pull from Personal Philosophy / Productivity & Systems wiki for principles when scoring Q34 ("what principles are we bending"). New: a Decision Log wiki page accumulates the narrative form of decisions over time (the decide archive is the structured form; the wiki page is the story).jab-hook — a Content Ideas wiki page hoppers hooks, frameworks, and stories. /jab-hook drafts pull candidates from there.slide-deck — content drafted in outputs/ becomes deck source; speaker notes can reference relevant wiki pages.pm — Projects/ folder in the vault is off-limits to second-brain; pm owns it. But a Workflow Docs wiki page captures operational patterns that show up across multiple projects.Two other systems following the same raw → wiki → outputs pattern. Both are worth watching as upgrade paths.
llm-wiki skill — off-the-shelf implementation of the 3-folder pattern. Pre-built workflows for compile / query / lint. Useful for comparing schema decisions.person- raw type + People wiki page) and scheduled maintenance (wire compile and lint to fire on a recurring schedule via the loop or compound-engineering:schedule skill).Projects/, Daily/, Templates/, Notes/, Tasks.md, Kanban.md, Home.md, or Inbox/ during second-brain operations. Those belong to other workflows.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 3,958 | 6,812 | +72% | 1 | 1 | 0% | 582 | 2,853 | +390% | 0 | 0 | — |
case-02 | fail→fail | 17,331 | 6,224 | -64% | 1 | 1 | 0% | 2,603 | 2,726 | +5% | 0 | 0 | — |
case-03 | fail→fail | 5,093 | 6,212 | +22% | 1 | 1 | 0% | 257 | 2,759 | +974% | 0 | 0 | — |
case-04 | fail→pass | 9,684 | 2,968 | -69% | 1 | 1 | 0% | 1,544 | 2,935 | +90% | 0 | 0 | — |
case-05 | fail→pass | 6,870 | 4,404 | -36% | 1 | 1 | 0% | 1,022 | 3,036 | +197% | 0 | 0 | — |
case-06 | pass→pass | 10,775 | 5,296 | -51% | 1 | 1 | 0% | 1,538 | 3,203 | +108% | 0 | 0 | — |
case-07 | fail→fail | 7,083 | 2,639 | -63% | 1 | 1 | 0% | 952 | 2,834 | +198% | 0 | 0 | — |
case-08 | fail→pass | 9,890 | 3,707 | -63% | 1 | 1 | 0% | 1,487 | 3,030 | +104% | 0 | 0 | — |
case-09 | pass→pass | 10,734 | 6,976 | -35% | 1 | 1 | 0% | 1,539 | 3,504 | +128% | 0 | 0 | — |
case-10 | pass→pass | 9,643 | 3,475 | -64% | 1 | 1 | 0% | 1,430 | 2,964 | +107% | 0 | 0 | — |
case-11 | pass→pass | 14,225 | 6,300 | -56% | 1 | 1 | 0% | 2,077 | 3,263 | +57% | 0 | 0 | — |
case-12 | fail→pass | 5,382 | 2,441 | -55% | 1 | 1 | 0% | 820 | 2,835 | +246% | 0 | 0 | — |
case-13 | pass→pass | 6,883 | 3,139 | -54% | 1 | 1 | 0% | 979 | 2,926 | +199% | 0 | 0 | — |
case-14 | pass→pass | 7,365 | 1,980 | -73% | 1 | 1 | 0% | 1,033 | 2,721 | +163% | 0 | 0 | — |
case-15 | fail→fail | 7,456 | 2,306 | -69% | 1 | 1 | 0% | 1,130 | 2,767 | +145% | 0 | 0 | — |
case-16 | pass→pass | 5,980 | 2,533 | -58% | 1 | 1 | 0% | 941 | 2,904 | +209% | 0 | 0 | — |
case-17 | fail→pass | 9,591 | 1,460 | -85% | 1 | 1 | 0% | 1,336 | 2,631 | +97% | 0 | 0 | — |
case-18 | fail→pass | 6,222 | 2,500 | -60% | 1 | 1 | 0% | 946 | 2,824 | +199% | 0 | 0 | — |
case-19 | fail→pass | 32,155 | 2,345 | -93% | 1 | 1 | 0% | 2,686 | 2,764 | +3% | 0 | 0 | — |
case-20 | fail→fail | 5,077 | 8,380 | +65% | 1 | 1 | 0% | 604 | 2,861 | +374% | 0 | 0 | — |
case-21 | fail→fail | 3,782 | 5,731 | +52% | 1 | 1 | 0% | 541 | 3,404 | +529% | 0 | 0 | — |
case-22 | fail→fail | 7,944 | 6,691 | -16% | 1 | 1 | 0% | 1,145 | 2,681 | +134% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 17 counted toward the lift figure. The other 5 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +32 percentage points is the difference between those two pass rates over the 17 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.