Skill Introduction

Overview

LLM Wiki — persistent markdown knowledge base that compounds across sessions (Karpathy model)

Core value

Turns reusable Debugging know-how into an installable skill, helping users complete github, community work faster.

Target users

Developers, testers, and maintainers who handle Debugging tasks in Focus Code.
Teams that already trust workflows or content from Yeachan-Heo.
Users who want standardized prompts, steps, or conventions instead of repeating setup work.

Best practices

Read the skill content first to confirm required inputs, expected outputs, and dependencies.
Try it on a small task before relying on it for critical work.
Add project-specific constraints such as coding style, target platform, test expectations, and delivery format.
For external sources, verify the source link, version, and recent maintenance activity.

Best use cases

Tasks related to github, community that need a reusable execution flow.
Converting a community repo, team convention, or personal workflow into day-to-day assistance.
Starting from a proven skill instead of writing prompts or procedures from scratch.

Limits and boundaries

Results depend on the quality of the original skill content and may need human correction.
It does not replace code review, tests, security review, or professional judgment.
External tools, APIs, account permissions, and local dependencies still need separate setup.

Differentiation

Structured around Debugging, making it easier to discover and reuse than loose prompt snippets.
Marked as GitHub, which helps users judge trust and maintenance expectations.
Keeps the original source link available for repository, documentation, or discussion follow-up.
Tagged with github, community, so it can be filtered by concrete task intent.

Detail Preview

SKILL.md

Primary filemarkdown3 KB

name: wiki description: LLM Wiki — persistent markdown knowledge base that compounds across sessions (Karpathy model) triggers: ["wiki", "wiki this", "wiki add", "wiki lint", "wiki query"]

Wiki

Persistent, self-maintained markdown knowledge base for project and session knowledge. Inspired by Karpathy's LLM Wiki concept.

Operations

Ingest

Process knowledge into wiki pages. A single ingest can touch multiple pages.

wiki_ingest({ title: "Auth Architecture", content: "...", tags: ["auth", "architecture"], category: "architecture" })

Query

Search across all wiki pages by keywords and tags. Returns matching pages with snippets — YOU (the LLM) synthesize answers with citations from the results.

wiki_query({ query: "authentication", tags: ["auth"], category: "architecture" })

Lint

Run health checks on the wiki. Detects orphan pages, stale content, broken cross-references, oversized pages, and structural contradictions.

wiki_lint()

Quick Add

Add a single page quickly (simpler than ingest).

wiki_add({ title: "Page Title", content: "...", tags: ["tag1"], category: "decision" })

List / Read / Delete

wiki_list()           # Show all pages (reads index.md)
wiki_read({ page: "auth-architecture" })  # Read specific page
wiki_delete({ page: "outdated-page" })    # Delete a page

Log

View wiki operation history by reading .omc/wiki/log.md.

Storage

Pages: .omc/wiki/*.md (markdown with YAML frontmatter)
Index: .omc/wiki/index.md (auto-maintained catalog)
Log: .omc/wiki/log.md (append-only operation chronicle)

Cross-References

Use [[page-name]] wiki-link syntax to create cross-references between pages.

Auto-Capture

At session end, significant discoveries are automatically captured as session-log pages. Configure via wiki.autoCapture in .omc-config.json (default: enabled).

Hard Constraints

NO vector embeddings — query uses keyword + tag matching only
Wiki pages are git-ignored by default (.omc/wiki/ is project-local)

wiki