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llm-wiki

LLM wiki kit

Created by Mehmet Goekce

Published in MehmetGoekce/llm-wiki. Publisher page

168 GitHub stars

What it is

Build Karpathy's LLM Wiki with Claude Code. L1/L2 cache architecture. Logseq + Obsidian support.
— the description by Mehmet Goekce

Summary from the brain’s metadata

Build Karpathy's LLM Wiki with Claude Code. L1/L2 cache architecture. Logseq + Obsidian support. Build Karpathy's LLM Wiki with Claude Code. Two-layer cache architecture (L1/L2). Supports Logseq and Obsidian.

How it works

Memory model: LLM wiki

AutoGineer overview, from the brain’s own files

Memory model: LLM wiki. Folders: .github (agent config, 5 files); docs (docs, 7 files); examples (examples, 2 files); templates (templates, 8 files).

Folders
FolderRoleFiles
.githubagent-config5
docsdocs7
examplesexamples2
templatestemplates8
.claude-pluginfolder3
openspecfolder23

Requirements

Works with: Claude Code

Set it up

  1. Clone the repository at the commit AutoGineer scanned:

    git clone https://github.com/MehmetGoekce/llm-wiki.git && cd llm-wiki && git checkout 5fa5ee7d49a4346eeb1d92c1de7bf649e7654e91
  2. Point Claude Code at .claude-plugin/icon.png: it does not read that file on its own.

  3. cd llm-wiki && claude

  4. AutoGineer scanned these files at commit 5fa5ee7.

  5. Not scanned by AutoGineerThe author’s README also describes installing it as a Claude Code plugin marketplace. Read its install section: AutoGineer did not scan that path. https://github.com/MehmetGoekce/llm-wiki/blob/5fa5ee7d49a4346eeb1d92c1de7bf649e7654e91/README.md#quick-start
  6. Not scanned by AutoGineerThe author’s README also describes installing it from a clone of its repository. Read its install section: AutoGineer did not scan that path. https://github.com/MehmetGoekce/llm-wiki/blob/5fa5ee7d49a4346eeb1d92c1de7bf649e7654e91/README.md#quick-start
  7. Created by Mehmet Goekce. Published in MehmetGoekce/llm-wiki. Licence: MIT License.

Usage

From the brain’s own files

  • ${user_config.wiki_path} (the "Wiki root:" line): your Logseq graph or Obsidian vault
  • ${CLAUDE_PLUGIN_ROOT} (the setup workflow): the clone, so that setup finds templates/

Documentation by Mehmet Goekce

llm-wiki

Image: License: MIT Image: Release Image: Stars Image: Top Language Image: Last Commit

Build Karpathy's LLM Wiki with Claude Code. Two-layer cache architecture (L1/L2). Supports Logseq and Obsidian.

graph TB
    subgraph "Every Session — Auto-loaded"
        L1[L1: Claude Memory]
        L1R[Rules & Gotchas]
        L1I[Identity & Preferences]
        L1C[Credentials]
        L1 --> L1R
        L1 --> L1I
        L1 --> L1C
    end

    subgraph "On Demand — /llm-wiki query"
        L2[L2: Wiki]
        L2P[Projects & History]
        L2W[Workflows & Processes]
        L2K[Research & Learning]
        L2 --> L2P
        L2 --> L2W
        L2 --> L2K
    end

    NEW[New Knowledge] --> ROUTE{Quick rule?}
    ROUTE -->|Yes| L1
    ROUTE -->|No| L2

    USER[User Query] --> CLAUDE[Claude Code]
    CLAUDE --> L1
    CLAUDE -->|Deep question| L2

What is this?

Image: Wiki graph view after setup Your wiki after a few ingests — interconnected knowledge pages in Logseq's graph view.

In April 2026, Andrej Karpathy published a gist called "LLM Wiki" that got 5,000+ stars in days. The idea: let an LLM maintain a structured, cross-referenced wiki for you. Feed it raw sources, it extracts facts, links them together, and keeps everything consistent. The wiki becomes a persistent, compounding artifact instead of a graveyard of stale notes.

Everyone loved the concept. Almost nobody built one. The gist describes what to build, not how to wire it up with real tools, real files, and real workflows. llm-wiki is the implementation. It uses Claude Code as the LLM brain and either Logseq or Obsidian as the wiki UI, with a two-layer cache architecture that turned out to be the key insight Karpathy's gist does not mention.

Why use this?

  • 5-minute setup. Install the plugin, run /llm-wiki setup, and you have a schema, namespaces, and git tracking. No manual design needed.

  • Claude becomes your wiki maintainer. /llm-wiki ingest updates 5-15 pages with cross-references from a single source.

  • L1/L2 architecture. Auto-loaded rules in memory (L1) + deep knowledge in the wiki (L2). No other tool has this.

  • Built-in quality checks. /llm-wiki lint finds orphan pages, stale content, broken refs, and credential leaks.

  • Logseq + Obsidian. Use whichever you already have. No tool switch required.

Quick Start

claude plugin marketplace add MehmetGoekce/llm-wiki
claude plugin install llm-wiki@mehmetgoekce

On Claude Code 2.1.275 or later, one line inside a session does the same:

/plugin install llm-wiki --marketplace MehmetGoekce/llm-wiki

Claude Code asks for one value, the Wiki root: your Logseq graph or Obsidian vault. The directory may be empty or not exist yet. Then, in any project:

/llm-wiki setup
/llm-wiki ingest "your first source"
/llm-wiki query "what do I know about X?"
/llm-wiki lint

/llm-wiki setup asks which tool you use and which namespaces you want, then creates the Schema, Dashboard, hub pages, Access-Log and llm-wiki.yml. The wiki starts sparse and gets denser with every ingest. New releases reach you through the plugin; nothing to copy.

Tested with Claude Code 2.1.296.

Without the plugin

Clone the repository and copy the skill into the project that should use it:

git clone https://github.com/MehmetGoekce/llm-wiki.git ~/llm-wiki
mkdir -p ~/myproject/.claude/commands
cp ~/llm-wiki/SKILL.md ~/myproject/.claude/commands/wiki.md

In the copy, replace two placeholders with absolute paths:

  • ${user_config.wiki_path} (the "Wiki root:" line): your Logseq graph or Obsidian vault

  • ${CLAUDE_PLUGIN_ROOT} (the setup workflow): the clone, so that setup finds templates/

On Linux (on macOS, write sed -i '' instead of sed -i):

sed -i -e 's|\${user_config.wiki_path}|/home/you/notes/wiki|g' \
       -e 's|\${CLAUDE_PLUGIN_ROOT}|/home/you/llm-wiki|g' \
       ~/myproject/.claude/commands/wiki.md

Then run /wiki setup in that project. The copy is invoked as /wiki <command>, stays at the version you copied, and needs the clone to stay where it is. The plugin is the recommended path.

The rest of this README writes /llm-wiki <command>. With a copied skill, type /wiki <command>.

Moving from a copied skill to the plugin

Install the plugin, enter your existing wiki directory as Wiki root, and delete the copied .claude/commands/wiki.md from your project. The wiki itself needs no change.

Coming from v1.6.0

The plugin's commands lost their second part: /llm-wiki:wiki ingest is now /llm-wiki ingest, and /llm-wiki:setup is now /llm-wiki setup. Update the plugin and use the new names.

The L1/L2 Architecture

This is the part not in Karpathy's gist, and it turned out to be the most important design decision.

When you start building a wiki, the instinct is to put everything in one place. That is wrong. Some knowledge must be available in every session, before you even ask a question -- things like "max 2-3 SSH calls to the VPS, never 10+" or "always use ISO 8601 dates." If the LLM has to query the wiki to learn these rules, it has already made the mistake.

Other knowledge only matters in specific contexts. The full history of a project. A detailed API workflow. Loading all of this into every session wastes the context window.

The solution maps to a concept every engineer knows: CPU cache hierarchy.

LayerWhatSizeLoadingContains
L1Claude Code Memory~10-20 filesAuto-loaded every sessionRules, gotchas, identity, credentials
L2Wiki (Logseq/Obsidian)~50-200 pagesOn-demand via /llm-wiki queryProjects, workflows, research, deep knowledge
graph TB
    subgraph "Every Session — Auto-loaded"
        L1[L1: Claude Memory]
        L1R[Rules & Gotchas]
        L1I[Identity & Preferences]
        L1C[Credentials]
        L1 --> L1R
        L1 --> L1I
        L1 --> L1C
    end

    subgraph "On Demand — /llm-wiki query"
        L2[L2: Wiki]
        L2P[Projects & History]
        L2W[Workflows & Processes]
        L2K[Research & Learning]
        L2 --> L2P
        L2 --> L2W
        L2 --> L2K
    end

    NEW[New Knowledge] --> ROUTE{Quick rule<br/>or gotcha?}
    ROUTE -->|Yes| L1
    ROUTE -->|No| L2

    USER[User Query] --> CLAUDE[Claude Code]
    CLAUDE --> L1
    CLAUDE -->|Deep question| L2

The routing rule is simple: Would the LLM making a mistake without this knowledge be dangerous or embarrassing? Then it belongs in L1. Would the mistake be merely inconvenient? Then L2.

Credentials are a special case -- they must live in L1 because the wiki is typically git-tracked. The L1 memory directory is excluded from git, making it the only safe place for secrets.

For the full deep-dive, see docs/l1-l2-architecture.md.

Commands

CommandDescription
/llm-wiki ingest <source>Process a source (URL, file, text), update 5-15 wiki pages
/llm-wiki query <question>Two-stage search via hub index, synthesize answer with source attribution
/llm-wiki prune [--months N]LRU-Demote: evict cold pages from the live index (default 6 months)
/llm-wiki prune --l1L1-Verification: classify L1 rules, check due behavior claims against local evidence, re-verify / demote / delete
/llm-wiki lint [--fix]Health check: orphans, stale pages, broken refs, index drift, credential leaks, due L1 claims
/llm-wiki statusMetrics dashboard: page count, health, hot/cold profile, recent changes
Ingest Flow

Ingest is the core operation. When you run /llm-wiki ingest "deployed v2.0 to production", here is what happens:

graph LR
    SRC[Source<br/>URL / File / Text] --> A[Phase 1<br/>Analyze & Extract]
    A --> B[Phase 2<br/>Scan Wiki<br/>Find affected pages]
    B --> C[Phase 3<br/>Update Pages<br/>Create new / Append]
    C --> D[Phase 4<br/>Quality Gate<br/>Properties? Cross-refs?<br/>No credentials?]
    D --> E[Phase 5<br/>Report<br/>Pages touched / Warnings]
    E --> GIT[git commit]

Phase 1 -- Analyze & Extract. Claude reads the source and extracts entities, facts, relationships, and dates. It classifies each piece by domain (business, technical, content, etc.) and checks whether it belongs in L1 (quick rule) or L2 (deep knowledge).

Phase 2 -- Scan Wiki. Claude reads the schema, then scans existing pages to find which ones the new information affects. If you mention a tool that already has an entity page, it knows to update that page too.

Phase 3 -- Update Pages. New pages get all required properties from the schema. Existing pages get new facts appended; when a fact supersedes a stated state (a status, a deadline, a decision), the block is rewritten and the old wording moves into a collapsed History -- nothing is deleted, and the current state stays on top. Target: 5-15 page touches per ingest.

Phase 4 -- Quality Gate. Before committing: Do all pages have required properties? Does every page have at least one cross-reference? Are there credential patterns in the content?

Phase 5 -- Report. Summary of pages created, updated, cross-references added, and any warnings.

Query

Query is two-stage, the way a CPU resolves an address before touching memory. Stage 1 (routing): Claude reads only the hub ### Index pages of the candidate namespaces — a cheap list of routing lines ([[page]] -- description #tags) — and picks the 3 most relevant pages by description. This is the wiki's page table. Stage 2 (read): it opens only those full pages and synthesizes an answer with source attribution. A full-text grep over every page is the L3 fallback, used only when routing finds nothing. Each full-page read is logged to an append-only Access-Log together with the routing reason it was picked (the matched index description or grep term) — so the log records not just what loaded but why, and it feeds prune. If the query reveals a gap, it offers to create a new page.

Prune

Prune is the eviction layer that keeps routing precise as the wiki grows. It reads the Access-Log, finds cold pages (no read in N months, default 6), and evicts them from the live index — the routing line moves from the hub ### Index to ### Archive and the page is marked archived::. This is demotion, not deletion: the file stays in place, every incoming [[link]] stays valid, and the page is still found by the L3 grep fallback (and re-promoted automatically if queried again). Crucially, prune never renames or moves a file — the wiki tool links by page name, so a move would break every backlink. Run it on a schedule (the command does not self-schedule).

--l1 is the L1 counterpart. Access frequency cannot find stale L1 rules — every L1 file loads every session, so a stale rule never looks cold; it shows up as the agent confidently acting on an outdated assumption. So L1 files carry a claim class: asserts-current-behavior: true for claims about a system's current state (a path, flag, version, quirk) and false for decisions and preferences, which never go stale. Behavior claims carry a verified date. /llm-wiki prune --l1 classifies unclassified files (it proposes, you confirm), checks due claims against read-only local evidence, and lets you re-verify, demote the rule to L2 as history, or delete it. It does not warn mid-session when a stale rule is about to justify an action — Claude Code loads L1, so there is no hook for that; it is on the roadmap.

Lint

Lint is the automated health check. It scans every wiki page and checks 13 rules: orphan pages (no incoming links), stale content (last updated 90+ days ago but still marked high-confidence), missing required properties, broken references, hub completeness, index drift (an active page with no routing line, or a routing line with no page), archived-in-live-index (a demoted page still routed), empty pages, weak cross-referencing, credential patterns, L1/L2 duplicates, due L1 claims (behavior claims whose verified date is missing or older than l1_verify_days), and block bloat (a block grown past 600 characters of prose, or an updated:: value used as a change log). Run with --fix and Claude auto-repairs what it can — including backfilling missing routing lines into hub indexes.

The Schema

The schema is the contract between you and the LLM. Without it, the LLM creates inconsistent pages -- one uses status: active, another state:: running, a third has no status field at all. With a schema, every page follows the same structure and automated quality checks become possible.

The schema defines:

  • 8 namespaces (Business, Tech, Content, Projects, People, Learning, Reference, Careers)

  • 5 page types (Entity, Project, Knowledge, Feedback, Hub) with required properties

  • Lint rules for automated health checks

  • L1/L2 boundary so the system knows where new knowledge should be routed

For the complete schema reference, see docs/schema-reference.md.

Logseq vs. Obsidian

Both wiki apps are supported. Choose based on your preference:

LogseqObsidian
Propertiesproperty:: value (inline)YAML frontmatter
FormatOutliner (- prefix on every line)Flat markdown
File namesWiki___Tech___Strapi.mdWiki/Tech/Strapi.md
Links[[Wiki/Tech/Strapi]][[Wiki/Tech/Strapi]]
BacklinksAutomatic (graph-native)Via plugin or core feature
Block addressingEvery line is a blockParagraph-level
LicenseAGPL-3.0 (open source)Proprietary (free for personal use)

Logseq shines when the LLM is doing the writing -- its outliner format means every block is independently addressable, so appending new content never disrupts existing structure.

Obsidian is better if you do a lot of manual editing -- flat markdown is more natural to write by hand, and the plugin ecosystem is massive.

For a detailed comparison with migration paths, see docs/logseq-vs-obsidian.md.

Before & After

The difference between a dead wiki and a living one is page quality.

Before -- a placeholder created when the page was first made:

- type:: knowledge
- domain:: content
- ## Newsletter
  - To be filled via /llm-wiki ingest.

After -- synthesized from multiple sources over several ingest operations:

- type:: knowledge
- domain:: content
- confidence:: high
- created:: 2026-03-15
- updated:: 2026-04-07
- ## Company Newsletter
  - Monthly newsletter targeting existing clients and prospects.
  - ### Metrics
    - | Metric | Value | As of |
      |--------|-------|-------|
      | Subscribers | ~240 | 2026-04-01 |
      | Open rate | 38% | 2026-04-01 |
      | Cadence | monthly | -- |
  - ### Content Strategy
    - 1 technical deep-dive + 1 business insight per issue
    - Always include a CTA to the latest blog post
    - Subject lines: question format performs 2x better
  - ### Open Questions
    - Segment list by industry vertical?
    - A/B test send time (Tuesday AM vs Thursday AM)?
  - ### Cross-References
    - [[Wiki/Content/Blog]] -- Source content
    - [[Wiki/Content/LinkedIn]] -- Promotion channel
    - [[Wiki/Reference/Workflows]] -- Publishing workflow

Every number has a date. Decisions have rationale. Open questions are explicit. Cross-references connect to related pages.

Configuration

Setup creates llm-wiki.yml in your wiki root. You can also create it manually:

# llm-wiki.yml

tool: logseq          # or "obsidian"
wiki_path: ~/Documents/MyWiki/
pages_dir: pages      # relative to wiki_path
memory_path: ~/.claude/projects/my-project/memory/
l1_verify_days: 90    # optional: re-verify L1 behavior claims after N days

namespaces:
  - Business
  - Tech
  - Content
  - Projects
  - People
  - Learning
  - Reference
  - Careers

# Lint settings
lint:
  stale_threshold_days: 90
  min_cross_refs: 1
  credential_patterns:
    - "token::"
    - "password::"
    - "secret::"
    - "api.key::"

# Ingest settings
ingest:
  target_page_touches: [5, 15]   # min, max pages per ingest
  append_only: true              # never delete content; superseded state moves to a collapsed History

# Language (for multilingual wikis)
language:
  business: en    # Language for business content
  tech: en        # Language for technical content

Trade-offs

No system is perfect. Some things to know:

  • The schema feels overengineered at first. With 10 pages, defining 5 page types and 8 lint rules seems like overkill. Past 50 pages, you will be grateful for the consistency. Define the schema early -- it is much harder to retrofit one later.

  • Two systems means you need a clear boundary. Having both L1 and L2 means you could accidentally put the same information in both places. The lint rule for L1/L2 duplicates exists precisely for this reason.

  • Parallel agents can conflict. If you have multiple Claude sessions writing to wiki files simultaneously, concurrent edits can cause conflicts. Treat wiki files as a shared resource.

  • Start with fewer hub pages. Let them emerge organically from ingest operations rather than creating empty hubs upfront.

Documentation

Privacy

llm-wiki has no backend and collects nothing. It is a skill and a few shell scripts that run inside your own Claude Code session.

  • Wiki pages, the access log and llm-wiki.yml are written to your local Logseq graph or Obsidian vault and stay there. Whatever you ingest ends up in those files, including names or contact details if the source contains them.

  • If you set memory_path, the skill also reads your local Claude Code memory directory: query may consult it, lint reports rules that are due for a check, and prune --l1 classifies, updates, moves or deletes memory files, each one only after you confirm it. lint never prints the content of a memory file. Without memory_path the skill does not touch that directory.

  • The skill and the scripts send nothing to the author or to any third party. There is no telemetry.

  • The only network access is the page fetch that ingest makes when you pass a URL as the source.

  • Commits are local. Nothing is pushed unless you push your wiki yourself.

  • Claude reads the content you work with in order to do the work. That processing is covered by your own Claude plan and Anthropic's terms, not by this plugin.

Credits

License

MIT -- see LICENSE for details.

docs/l1-l2-architecture.md

The L1/L2 Architecture

This is the part that is not in Karpathy's gist, and it turned out to be the most important design decision in the entire system.

The Discovery

When you first start building an LLM wiki, the plan seems simple: put everything in one place. All your project notes, coding rules, deployment gotchas, personal preferences -- one system to rule them all.

It takes about a day to realize this is wrong.

Some knowledge must be available in every single session, before you even ask a question. Things like "always use ISO 8601 date format" or "max 2-3 SSH calls to the server, never 10+, or you risk an OOM reboot." If the LLM has to query the wiki to learn these rules, it has already made the mistake. The damage is done by the time the knowledge is retrieved.

Other knowledge only matters in specific contexts. The full history of a blog series. The detailed API publishing workflow. The evaluation of a marketing strategy. Loading all of this into every session would waste the context window and slow things down.

You need two layers. The solution maps to a concept every engineer knows.

The CPU Cache Metaphor

In a CPU, L1 cache is tiny but blazing fast -- data the processor needs on every cycle. L2 cache is larger but slower -- data that is important but not needed constantly. Main memory is huge but comparatively glacial.

The same principle applies to LLM knowledge:

CPU CacheLLM Wiki
L1~64 KB, 1 cycle latency~10-20 files, auto-loaded every session
L2~256 KB, 10 cycle latency~50-200 pages, queried on demand
Main memoryGBs, 100+ cycle latencyThe internet, your email, Confluence, Jira
graph TB
    subgraph "L1 — Claude Code Memory (auto-loaded)"
        L1R[Rules & Gotchas<br/><i>Max 3 SSH calls, date format, etc.</i>]
        L1I[Identity & Preferences<br/><i>Name, address, communication style</i>]
        L1C[Credentials & Secrets<br/><i>API tokens, passwords — git-excluded</i>]
    end

    subgraph "L2 — Wiki (on-demand)"
        L2P[Projects & History<br/><i>Timelines, decisions, status</i>]
        L2W[Workflows & Processes<br/><i>Publishing, deployment, onboarding</i>]
        L2K[Research & Learning<br/><i>Tech evaluations, book notes, courses</i>]
        L2B[Business Intelligence<br/><i>Client details, strategy, market analysis</i>]
    end

    subgraph "Main Memory — External Sources"
        EXT1[Email / Slack]
        EXT2[Jira / Confluence]
        EXT3[The Internet]
    end

    CLAUDE[Claude Code Session] -->|Always has| L1R
    CLAUDE -->|Always has| L1I
    CLAUDE -->|Always has| L1C
    CLAUDE -->|/llm-wiki query| L2P
    CLAUDE -->|/llm-wiki query| L2W
    CLAUDE -->|/llm-wiki query| L2K
    CLAUDE -->|/llm-wiki query| L2B
    CLAUDE -->|/llm-wiki ingest| EXT1
    CLAUDE -->|/llm-wiki ingest| EXT2
    CLAUDE -->|/llm-wiki ingest| EXT3

The Routing Rule

When new knowledge comes in, how do you decide where it goes? The rule is simple:

Would the LLM making a mistake without this knowledge be dangerous or embarrassing? Then it belongs in L1 -- auto-loaded every session, zero-query latency.

Would the mistake be merely inconvenient? Then it belongs in L2 -- queried on demand when the context requires it.

Some examples:

KnowledgeConsequence of not knowingLayer
"Always use ISO 8601 dates"Inconsistent dates across all outputL1
"Server has 2GB RAM, max 3 SSH calls"OOM reboot in productionL1
"Business address changed to X"Wrong address on proposalsL1
"Deploy script requires clean git state"Failed deploys, wasted timeL1
"Blog series has 3 published parts"Inaccurate count, easily correctedL2
"Evaluated 4 marketing strategies in Q1"Missing context, ask to clarifyL2
"Book outline has 12 chapters"Wrong chapter count, quickly fixableL2
"Client project started 2025-06-01"Incorrect timeline, no real harmL2

The pattern is clear: L1 holds operational guardrails -- things that prevent mistakes in the moment. L2 holds contextual knowledge -- things that enrich answers when relevant.

Credential Safety

Credentials deserve special attention because they sit at the intersection of two constraints:

  1. They must be in L1 because the LLM needs them without querying (e.g., API tokens for deployment scripts).

  2. They must never be in L2 because the wiki is typically git-tracked.

This is not just a preference -- it is a hard security boundary. The L1 memory directory lives at a path like ~/.claude/memory/ which is excluded from version control via .gitignore. The L2 wiki lives in your Logseq or Obsidian graph, which you likely sync or commit to a repository.

The lint rule credential-leak exists to enforce this boundary. It scans all wiki pages for patterns like token::, password::, secret::, and api-key::. If it finds a match, it flags it as a critical issue.

credential_patterns:
  - "token::"
  - "password::"
  - "secret::"
  - "api.key::"
  - "api-key::"
  - "[A-Za-z0-9+/]{40,}"   # Base64 strings that look like tokens

The rule is absolute: if it is a secret, it goes in L1. Period.

L1 in Practice: Claude Code Memory

In Claude Code, L1 maps to two mechanisms:

  1. CLAUDE.md -- A project-level instruction file loaded automatically at session start. Contains high-level project context, tech stack, and links to skills.

  2. memory/ directory -- Persistent memory files that Claude Code loads every session. Each file covers one topic: a gotcha, a preference, a credential reference.

A typical L1 memory directory looks like this:

memory/
  MEMORY.md              # Index file — points to L2 wiki for deep queries
  feedback_deploy_ram.md # "Stop X before deploy to prevent OOM"
  feedback_ssh_batch.md  # "Max 2-3 SSH calls, never 10+"
  user_name.md           # Name spelling and preferences
  user_address.md        # Current business address
  reference_creds.md     # API tokens and passwords (git-excluded!)

The total size is small -- typically under 20 files, each a few lines. This is deliberate. L1 should be scannable in a fraction of a second. If your L1 grows past ~30 files, it is time to audit and move contextual knowledge to L2.

L2 in Practice: The Wiki

L2 is the wiki itself -- dozens to hundreds of structured pages organized by namespace. Unlike L1, these pages are only loaded when relevant. A /llm-wiki query "what is the status of project X?" triggers Claude to read 3-5 relevant pages, not all 100.

The key properties of L2:

  • Structured: Every page follows the schema (required properties, page types, cross-references).

  • Searchable: Namespaces and properties make it easy for the LLM to find relevant pages.

  • Nothing is deleted: New information is appended. When a fact supersedes a stated state, that block is rewritten and the old wording moves, dated, into its collapsed History.

  • Versioned: Every change is git-committed with a description of what was ingested.

The L1/L2 Boundary in the Schema

The schema explicitly defines the boundary so the system can self-enforce it:

## L1/L2 Boundary
- L1 (Memory): Rules, gotchas, identity, credentials
- L2 (Wiki): Projects, workflows, research, deep knowledge
- Same info in both? → Lint warning

This is not just documentation -- the /llm-wiki lint command actively checks for L1/L2 duplicates. If the same rule appears in both a memory file and a wiki page, it flags a warning. Duplicates mean one copy will eventually go stale, leading to contradictory knowledge.

Evolving the Boundary

The L1/L2 boundary is not static. As your wiki grows, some knowledge migrates:

  • L2 to L1: You discover a lesson the hard way three times. Time to promote it from "project context" to "always-loaded rule."

  • L1 to L2: A credential is rotated and the old one is removed. The history of why it was rotated is L2 material.

  • Merge: Two L1 files cover related gotchas. Combine them into one to keep L1 lean.

  • Archive: A project completes. Its L1 gotchas become L2 historical notes.

/llm-wiki lint flags L1/L2 duplicates that need resolution. Promotion from L2 to L1 is still a manual decision. Demotion out of L1 has its own mechanism, described next.

Keeping L1 Honest: Claim Class + Verification

Access-based eviction (/llm-wiki prune) only covers L2. Every L1 file loads every session, so "last used" carries no signal: a stale L1 rule never looks cold. It shows up as the agent confidently acting on an outdated assumption.

So L1 staleness is tied to what kind of claim a rule makes, not to how often it is read. Each L1 file can carry one frontmatter key:

  • asserts-current-behavior: true — a falsifiable claim about the current state of a system: a path, command, flag, version, port, or tool quirk. "PM2 reload does not work with npm start." These can go stale without anyone touching the rule.

  • asserts-current-behavior: false — a decision, preference, identity fact, or rationale. "No AI attribution in commits." These never go stale.

Behavior claims also carry verified: <date>. A claim is due when it was never verified or the date is older than l1_verify_days (default 90). How many files that is depends on how you use L1. A lean L1 of decisions and preferences has few; an L1 that accumulated gotchas and project state has many. In a 15-file pilot on a long-lived L1, 12 were behavior claims, and one was project state that belonged in L2 all along.

The loop:

  1. /llm-wiki lint (Rule 12) reports due claims and the number of unclassified files. It never writes to L1 and never prints L1 file bodies — L1 may hold credentials.

  2. /llm-wiki prune --l1 classifies unclassified files in batches (it proposes, you confirm), then checks due claims against read-only, local evidence: does the path exist, does --help still list the flag, does the dependency manifest still pin that version. Each claim inside a rule gets its own verdict — supports, contradicts, or inconclusive (e.g. pricing or third-party behavior that cannot be checked locally) — with its basis: a read-only command, the implementing source code, or a file check. Rules usually bundle several claims, so partial verdicts are normal and marked as such.

  3. You decide per rule: re-verify (stamps verified; on a contradiction only together with a corrected rule text), demote to L2 (the rule becomes a history block on the matching wiki page, then the L1 file and its index line are removed), or delete. A correction reaches everywhere the claim is loaded from: body, description, and the index line. Before a file is removed, references to it from other L1 files are rewritten or listed. L1 is not git-tracked, so nothing is written without confirmation, and you see what carries over to L2 and what is dropped before removal. Credential rules are never demoted to L2.

What this does not do (yet): warn at the moment a due rule is about to justify an action. Claude Code loads L1, not llm-wiki, so there is no hook to enforce such a gate. A due rule is caught on the next lint / prune --l1 run, not mid-session. A planning-vs-action gate — soft note when a stale rule informs planning, loud warning when it justifies a write — is on the roadmap.

The goal is a lean L1 and a rich L2. Keep the fast cache small and hot. Let the wiki grow without bounds.

58 files · 2 not served here

Advantages

  • 5-minute setup. Install the plugin, run /llm-wiki setup, and you have a schema, namespaces, and git tracking. No manual design needed. evidence: README.md
  • Claude becomes your wiki maintainer. /llm-wiki ingest updates 5-15 pages with cross-references from a single source. evidence: README.md
  • L1/L2 architecture. Auto-loaded rules in memory (L1) + deep knowledge in the wiki (L2). No other tool has this. evidence: README.md
  • Built-in quality checks. /llm-wiki lint finds orphan pages, stale content, broken refs, and credential leaks. evidence: README.md
  • Logseq + Obsidian. Use whichever you already have. No tool switch required. evidence: README.md

Limitations

  • The schema feels overengineered at first. With 10 pages, defining 5 page types and 8 lint rules seems like overkill. Past 50 pages, you will be grateful for the consistency. Define the schema early -- it is much harder to retrofit one later. evidence: README.md
  • Two systems means you need a clear boundary. Having both L1 and L2 means you could accidentally put the same information in both places. The lint rule for L1/L2 duplicates exists precisely for this reason. evidence: README.md
  • Parallel agents can conflict. If you have multiple Claude sessions writing to wiki files simultaneously, concurrent edits can cause conflicts. Treat wiki files as a shared resource. evidence: README.md
  • Start with fewer hub pages. Let them emerge organically from ingest operations rather than creating empty hubs upfront. evidence: README.md

Security

Risk level: No risk found

This brain runs

Agent instructions that run or fetch something (18)

  • SKILL.md: Run /llm-wiki setup to create one." If its `wiki_path` names a different directory than the wiki root above, warn once, naming both paths, and continue with the wiki root above.
  • SKILL.md: Meant as a periodic run (default cadence N = 6 months) — wire it via your scheduler;
  • SKILL.md: READ-ONLY and LOCAL: check existence, read files, search contents, read dependency manifests, run commands only with `--version` / `--help`.
  • SKILL.md: Evidence basis per claim: `executed` (read-only command), `source` (read the implementing code, not run), or `file` (existence/content).
  • SKILL.md: Skip -> file untouched, stays due for the next run
  • SKILL.md: Timestamp the lint run
  • SKILL.md: Last prune run (newest archived:: date) + a recommendation when the cold-page count is high
  • SKILL.md: Comparison to last status run (if Dashboard page exists)
  • SKILL.md: git: if the user wants git init or the root is a repository, check `git --version`.
  • SKILL.md: Run `date +%Y-%m-%d` once.
  • SKILL.md: Git init, only if the user agreed and the root has no `.git`: `git -C "<root>" init`.
  • SKILL.md: Commit, only if the root is a git repository and this run created at least one file.
  • SKILL.md: Run lint on imported pages
  • SKILL.md: decision:: run benchmark B1 first, then delete (2026-09-12)
  • SKILL.md: - **Next step:** run B1, otherwise default A (check volumes, delete)
  • SKILL.md: status: open · ticket: OPS-195 · decision: run benchmark B1 first, then delete (2026-09-12)
  • SKILL.md: **Next step:** run B1, otherwise default A (check volumes, delete)
  • openspec/AGENTS.md: git is optional.

Attribution and licence

Created by
Mehmet Goekce
Declared authors
Publisher
Mehmet Gökçe (Community)
Source
MehmetGoekce/llm-wiki · commit 5fa5ee7
Licence
MIT License (files served here)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Mehmet Goekce.

Install from source

2 of its files are not served here, so there is no ZIP. MehmetGoekce/llm-wiki at 5fa5ee7