Karpathy's LLM Wiki — build and maintain a persistent, interlinked markdown knowledge base. Ingest sources, query compiled knowledge, and lint for consistency.
Scanned 9/9/2026
Install to Claude Code
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---
name: llm-wiki
description: "Karpathy's LLM Wiki — build and maintain a persistent, interlinked markdown knowledge base. Ingest sources, query compiled knowledge, and lint for consistency."
version: 3.0.0
author: Hermes Agent
license: MIT
metadata:
hermes:
tags: [wiki, knowledge-base, research, notes, markdown, rag-alternative, batch-ingest]
category: research
related_skills: [obsidian, arxiv, agentic-research-ideas]
config:
- key: wiki.path
description: Path to the LLM Wiki knowledge base directory
default: "~/wiki"
prompt: Wiki directory path
---
# Karpathy's LLM Wiki
Build and maintain a persistent, compounding knowledge base as interlinked markdown files.
Based on [Andrej Karpathy's LLM Wiki pattern](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f).
Unlike traditional RAG (which rediscovers knowledge from scratch per query), the wiki
compiles knowledge once and keeps it current. Cross-references are already there.
Contradictions have already been flagged. Synthesis reflects everything ingested.
**Division of labor:** The human curates sources and directs analysis. The agent
summarizes, cross-references, files, and maintains consistency.
## When This Skill Activates
Use this skill when the user:
- Asks to create, build, or start a wiki or knowledge base
- Asks to ingest, add, or process a source into their wiki
- Asks a question and an existing wiki is present at the configured path
- Asks to lint, audit, or health-check their wiki
- References their wiki, knowledge base, or "notes" in a research context
- Wants to batch-ingest hundreds/thousands of documents into wiki format
## Wiki Location
Configured via `skills.config.wiki.path` in `~/.hermes/config.yaml` (prompted
during `hermes config migrate` or `hermes setup`):
```yaml
skills:
config:
wiki:
path: ~/wiki
```
Falls back to `~/wiki` default. The resolved path is injected when this
skill loads — check the `[Skill config: ...]` block above for the active value.
Before setting `wiki.path`, verify the target actually exists. A stale default like
`~/wiki` is easy to leave behind even when the real wiki lives elsewhere.
For the workspace-hub multi-wiki layout, the preferred root is usually:
```yaml
skills:
config:
wiki:
path: /mnt/local-analysis/workspace-hub/knowledge/wikis
```
This points at the domain-wiki root (`engineering/`, `marine-engineering/`,
`maritime-law/`, `naval-architecture/`, etc.) rather than a single flat `~/wiki`
folder.
The wiki is just a directory of markdown files — open it in Obsidian, VS Code, or
any editor. No database, no special tooling required.
## CLI Tool (workspace-hub)
The `llm-wiki` CLI at `scripts/knowledge/llm_wiki.py` provides 6 commands for
operating wikis programmatically. All commands use the pattern:
```bash
uv run scripts/knowledge/llm_wiki.py <command> --wiki <domain>
```
| Command | Purpose |
|---------|---------|
| `init <domain>` | Scaffold a new domain wiki under `knowledge/wikis/<domain>/` |
| `status --wiki <d>` | Report page counts, source counts, link density |
| `ingest <file> --wiki <d>` | Copy source file + generate LLM processing instructions |
| `query "..." --wiki <d>` | Keyword search across wiki pages with relevance ranking |
| `lint --wiki <d>` | Health checks (orphans, empty pages, index consistency, link density) |
| `batch-ingest <file> --wiki <d> --batch-size N` | Bulk-create source pages from metadata JSONL/JSON/YAML |
**batch-ingest** is designed for scale:
- Checkpoint-based resume (`.checkpoint.jsonl` in wiki root)
- `--dry-run` for preview
- Progress reporting every batch
- Skips already-processed records
- Used to ingest 22K conference papers → 12K source pages in one run
- Proven: 100 records/batch, ~400 records per 10 seconds
Location: `knowledge/wikis/<domain>/` (not `~/wiki`). This is a multi-wiki
ecosystem — multiple domain wikis coexist under `knowledge/wikis/`. Force-add
to git despite `.gitignore` since wiki content is the compounding artifact.
## Architecture
### Multi-Wiki Pattern
In workspace-hub, wikis are organized as a multi-domain ecosystem under
`knowledge/wikis/<domain>/`, not a single `~/wiki`. Each domain
(marine-engineering, maritime-law, naval-architecture) has its own
complete three-layer structure. Cross-wiki linking connects related topics
across domains.
### Three Layers (per domain wiki)
```
knowledge/wikis/<domain>/
├── AGENTS.md # Schema: conventions, structure rules, domain config
├── raw/ # Layer 1: Immutable source material
│ ├── papers/ # PDFs, standards, papers
│ ├── standards/ # Standards documents
│ ├── articles/ # Web articles, clippings
│ └── assets/ # Images, diagrams
└── wiki/ # Layer 2: The LLM-maintained wiki
├── index.md # Content catalog with sectioned entries
├── log.md # Chronological action log (append-only)
├── overview.md # Domain synthesis summary
├── entities/ # Entity pages (things: equipment, orgs, vessels)
├── concepts/ # Concept pages (ideas: methods, principles)
├── sources/ # Source summary pages (one per ingested document)
├── comparisons/ # Filed query outputs
└── visualizations/ # matplotlib plots, Marp slide decks
```
**Layer 1 — Raw Sources:** Immutable. The agent reads but never modifies these.
**Layer 2 — The Wiki:** Agent-owned markdown files. Created, updated, and
cross-referenced by the agent.
**Layer 3 — The Schema:** `AGENTS.md` defines structure, conventions, and tag taxonomy.
### Scaling Pattern (learned from 12K+ source ingestion)
- **Metadata-first approach**: Don't extract PDF content (hits 5-min timeouts on
large files). Instead, read structured metadata (titles, topics, sizes) and
create wiki source pages.
- **Proven at scale**: 22K conference metadata records → 12K unique source pages,
skipping 10K+ duplicates via checkpoint file.
- **Batch size**: 100 records per batch, progress reported every batch.
- **Checkpoint resume**: `.checkpoint.jsonl` tracks processed records by unique ID.
- **Index management**: Updates index.md after each batch, not after every record.
- **Git considerations**: Wiki pages must be force-added (`git add -f`) even if
`.gitignore` excludes the wikis directory. Wiki content is the compounding artifact.
- **Workspace-hub hook gotcha**: `knowledge/wikis/<domain>/AGENTS.md` files are wiki schema/config files generated by `llm-wiki init`, not harness adapter files. If the repo hook `.Codex/hooks/check-Codex-md-limits.sh` applies the 20-line harness limit to all `AGENTS.md` paths, commits touching wiki `AGENTS.md` can fail with a false positive. The minimal safe fix is to exclude `^knowledge/wikis/` from that hook's staged-file filter so harness limits still apply to real adapter files while wiki schema files remain editable.
## Resuming an Existing Wiki (CRITICAL — do this every session)
When the user has an existing wiki, **always orient yourself before doing anything**:
① **Read `AGENTS.md`** (or `SCHEMA.md`) — understand the domain, conventions, and tag taxonomy.
② **Read `index.md`** — learn what pages exist and their summaries.
③ **Scan recent `log.md`** — read the last 20-30 entries to understand recent activity.
```bash
WIKI="${wiki_path:-$HOME/wiki}"
# Orientation reads at session start
read_file "$WIKI/SCHEMA.md"
read_file "$WIKI/index.md"
read_file "$WIKI/log.md" offset=<last 30 lines>
```
Only after orientation should you ingest, query, or lint. This prevents:
- Creating duplicate pages for entities that already exist
- Missing cross-references to existing content
- Contradicting the schema's conventions
- Repeating work already logged
For large wikis (100+ pages), also run a quick `search_files` for the topic
at hand before creating anything new.
## Initializing a New Wiki (via CLI)
```bash
uv run scripts/knowledge/llm_wiki.py init <domain>
```
This scaffolds the full three-layer structure, creates `AGENTS.md` with
domain-specific schema, initializes `index.md` and `log.md`, and creates
the `raw/` and `wiki/` subdirectories.
After scaffolding:
1. Add some sources: `ingest <file> --wiki <domain>`
2. For bulk: `batch-ingest metadata.jsonl --wiki <domain> --batch-size 100`
3. Check health: `lint --wiki <domain>`
## Core Operations
### 1. Ingest
When the user provides a source (URL, file, paste), integrate it into the wiki:
① **Capture the raw source:**
- URL → use `web_extract` to get markdown, save to `raw/articles/`
- PDF → use `web_extract` (handles PDFs), save to `raw/papers/`
- Pasted text → save to appropriate `raw/` subdirectory
- Name the file descriptively: `raw/articles/karpathy-llm-wiki-2026.md`
② **Discuss takeaways** with the user — what's interesting, what matters for
the domain. (Skip this in automated/cron contexts — proceed directly.)
③ **Check what already exists** — search index.md and use `search_files` to find
existing pages for mentioned entities/concepts. This is the difference between
a growing wiki and a pile of duplicates.
④ **Write or update wiki pages:**
- **New entities/concepts:** Create pages only if they meet the Page Thresholds
in SCHEMA.md (2+ source mentions, or central to one source)
- **Existing pages:** Add new information, update facts, bump `updated` date.
When new info contradicts existing content, follow the Update Policy.
- **Cross-reference:** Every new or updated page must link to at least 2 other
pages via `[[wikilinks]]`. Check that existing pages link back.
- **Tags:** Only use tags from the taxonomy in SCHEMA.md
⑤ **Update navigation:**
- Add new pages to `index.md` under the correct section, alphabetically
- Update the "Total pages" count and "Last updated" date in index header
- Append to `log.md`: `## [YYYY-MM-DD] ingest | Source Title`
- List every file created or updated in the log entry
⑥ **Report what changed** — list every file created or updated to the user.
A single source can trigger updates across 5-15 wiki pages. This is normal
and desired — it's the compounding effect.
### 2. Query
When the user asks a question about the wiki's domain:
① **Read `index.md`** to identify relevant pages.
② **For wikis with 100+ pages**, also `search_files` across all `.md` files
for key terms — the index alone may miss relevant content.
③ **Read the relevant pages** using `read_file`.
④ **Synthesize an answer** from the compiled knowledge. Cite the wiki pages
you drew from: "Based on [[page-a]] and [[page-b]]..."
⑤ **File valuable answers back** — if the answer is a substantial comparison,
deep dive, or novel synthesis, create a page in `queries/` or `comparisons/`.
Don't file trivial lookups — only answers that would be painful to re-derive.
⑥ **Update log.md** with the query and whether it was filed.
### 3. Lint
When the user asks to lint, health-check, or audit the wiki:
① **Orphan pages:** Find pages with no inbound `[[wikilinks]]` from other pages.
```python
# Use execute_code for this — programmatic scan across all wiki pages
# Scan all .md files in entities/, concepts/, comparisons/, queries/
# Extract all [[wikilinks]] — build inbound link map
# Pages with zero inbound links are orphans
```
② **Broken wikilinks:** Find `[[links]]` that point to pages that don't exist.
③ **Index completeness:** Every wiki page should appear in `index.md`. Compare
the filesystem against index entries.
④ **Frontmatter validation:** Every wiki page must have all required fields
(title, created, updated, type, tags, sources). Tags must be in the taxonomy.
⑤ **Stale content:** Pages whose `updated` date is >90 days older than the most
recent source that mentions the same entities.
⑥ **Contradictions:** Pages on the same topic with conflicting claims. Look for
pages that share tags/entities but state different facts.
⑦ **Page size:** Flag pages over 200 lines — candidates for splitting.
⑧ **Tag audit:** List all tags in use, flag any not in the SCHEMA.md taxonomy.
⑨ **Log rotation:** If log.md exceeds 500 entries, rotate it.
⑩ **Report findings** with specific file paths and suggested actions, grouped by
severity (broken links > orphans > stale content > style issues).
⑪ **Append to log.md:** `## [YYYY-MM-DD] lint | N issues found`
### 4. Bulk Ingest (CLI-based)
For large-scale ingestion (100+ sources), use the `llm-wiki batch-ingest` CLI:
```bash
# Dry-run first to preview
uv run scripts/knowledge/llm_wiki.py batch-ingest metadata.jsonl --wiki <domain> --batch-size 100 --dry-run
# Then run for real (resume-safe via .checkpoint.jsonl)
uv run scripts/knowledge/llm_wiki.py batch-ingest metadata.jsonl --wiki <domain> --batch-size 100
```
The CLI handles:
- ✅ Checkpoint-based resume (safe to interrupt/restart)
- ✅ Progress reporting every batch — 100 records per batch at ~400 records per 10s
- ✅ Skip already-processed records (10K+ duplicates in a 22K run)
- ✅ Batch index.md/log.md updates (efficient)
- ✅ `--dry-run` mode to preview filenames and counts
### 5. Seed Migration (YAML → Wiki)
For structured YAML knowledge seeds in `knowledge/seeds/`:
1. Parse the YAML to extract entries
2. Group entries by domain/category
3. For each entry: create entity/concept/source page
4. Cross-link with existing wiki pages
5. Update index.md with all migrated entries
6. Append structured entries to log.md
Proven pattern: 18 mooring failure entries → 4 wiki pages (source + 2 concepts + 1 entity)
10 law cases + 6 conventions → 20 wiki pages with cross-references
## Working with the Wiki
### Searching
```bash
# Find pages by content
search_files "transformer" path="$WIKI" file_glob="*.md"
# Find pages by filename
search_files "*.md" target="files" path="$WIKI"
# Find pages by tag
search_files "tags:.*alignment" path="$WIKI" file_glob="*.md"
# Recent activity
read_file "$WIKI/log.md" offset=<last 20 lines>
```
### Seed Migration Pattern
For structured YAML seeds (like `knowledge/seeds/naval-architecture-resources.yaml`):
1. **Parse YAML categories** (textbooks, hydrostatics, portals, ship plans, etc.)
2. **Create concept pages** for each major topic domain (5-6 pages)
3. **Create source pages** for each individual resource (17-36 pages per seed)
4. **Update index.md** with structured tables
5. **Update log.md** with migration entry
This approach is much faster than full PDF extraction and creates structured
wiki pages that can be enhanced later with LLM content.
### Cross-Wiki Linking
When managing multiple domain wikis, look for natural connections:
- Deepwater Horizon → marine-engineering (lng-carrier-mooring) + maritime-law (OPA 90)
- Mooring failures → marine-eng + naval-arch stability concepts
- Classification rules → naval-arch + maritime-law liability conventions
## Obsidian Integration
The wiki directory works as an Obsidian vault out of the box:
- `[[wikilinks]]` render as clickable links
- Graph View visualizes the knowledge network
- YAML frontmatter powers Dataview queries
- The `raw/assets/` folder holds images referenced via `![[image.png]]`
For best results:
- Set Obsidian's attachment folder to `raw/assets/`
- Enable "Wikilinks" in Obsidian settings (usually on by default)
- Install Dataview plugin for queries like `TABLE tags FROM "entities" WHERE contains(tags, "company")`
## Pitfalls
- **Automated wiki health cron gotchas** — For workspace-hub `scripts/knowledge/wiki_health_cron.py` runs, verify the domain list before trusting the report. Hidden/operational directories under `knowledge/wikis/` (for example `.planning/`) are not domain wikis and should be skipped. Directories that contain only `AGENTS.md` or otherwise lack `wiki/` should be reported as critical missing scaffold/index/log issues, not allowed to crash the cron before reports are written. Health reports under `knowledge/wikis/health-reports/` may be ignored by `.gitignore`; use `git add -f knowledge/wikis/health-reports/health-YYYY-MM-DD.{json,md}` when committing them.
- **Never modify files in `raw/`** — sources are immutable. Corrections go in wiki pages.
- **Always orient first** — read SCHEMA + index + recent log before any operation in a new session.
Skipping this causes duplicates and missed cross-references.
- **Always update index.md and log.md** — skipping this makes the wiki degrade. These are the
navigational backbone.
- **Don't create pages for passing mentions** — follow the Page Thresholds in SCHEMA.md. A name
appearing once in a footnote doesn't warrant an entity page.
- **Don't create pages without cross-references** — isolated pages are invisible. Every page must
link to at least 2 other pages.
- **Frontmatter is required** — it enables search, filtering, and staleness detection.
- **Tags must come from the taxonomy** — freeform tags decay into noise. Add new tags to SCHEMA.md
first, then use them.
- **Keep pages scannable** — a wiki page should be readable in 30 seconds. Split pages over
200 lines. Move detailed analysis to dedicated deep-dive pages.
- **Ask before mass-updating** — if an ingest would touch 10+ existing pages, confirm
the scope with the user first.
- **Rotate the log** — when log.md exceeds 500 entries, rename it `log-YYYY.md` and start fresh.
The agent should check log size during lint.
- **Handle contradictions explicitly** — don't silently overwrite. Note both claims with dates,
mark in frontmatter, flag for user review.
- **PDF extraction timeout** — Large PDFs hit 5-min sandbox timeouts. Use metadata-first
approach for speed. Full extraction = enhancement when async workers exist.
- **Git force-add required** — Wiki dirs may be in `.gitignore`. Use `git add -f` to commit
content. Wiki content is the compounding artifact and must be tracked.
- **Batch size trade-off** — 100 records/batch balances speed with index update frequency.
Smaller = more frequent updates, slower. Larger = fewer index commits, risk more on crash.
- **Low link density early** — Newly created wikis naturally have low link density.
This resolves as cross-references grow during normal ingest operations.
- **YAML seed migration is fast** — Converting structured YAML to wiki pages is 10x faster
than PDF extraction. Use this pattern whenever seeds exist.Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
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