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LLM-WIKI Standard

@dowonk-7949/llm-wiki-standard is a zero-dependency CLI that builds and validates a standardized, source-backed knowledge base (docs/llm-wiki/) for AI coding agents — so an agent starts from one index instead of re-reading your whole codebase on every task.

Without LLM-WIKI:  task -> re-scan the codebase -> re-derive structure & rules -> work
With LLM-WIKI:     task -> read index.md -> read the relevant wiki docs -> inspect only the needed source -> work

The CLI creates the safe structure and guardrails; an agent (Codex, Claude Code, …) enriches the docs from real code; a human reviews and approves verified; CI keeps it honest. Useful for legacy maintenance, feature work, incident response, onboarding, handovers, and sharing project knowledge across agents.

Supported environments

| | | | --- | --- | | Runtime | Node.js ≥ 18.18.0 · Windows, macOS, Linux | | Dependencies | none — no runtime third-party dependencies | | Detects | Node · Python · Go · Rust · JVM · PHP · Ruby · .NET · mobile (Android / Flutter / iOS / React Native) · infra (Docker / Compose / Kubernetes / Helm / Terraform) | | Agents / editors | Codex (AGENTS.md), Claude Code (CLAUDE.md), Cursor, GitHub Copilot, Windsurf, Gemini CLI — plus any MCP client via llm-wiki mcp | | Standalone | the CLI (init / validate / audit / graph / stats / CI) works fully without any agent |

Quick start

npm install -D @dowonk-7949/llm-wiki-standard
npx llm-wiki quickstart --write --type frontend --agent claude   # or --agent codex

quickstart --write detects the project, creates the wiki + adapter files, and prints a handoff prompt. Paste that prompt into your agent: it reads docs/llm-wiki/index.md, enriches the docs from real source files, and leaves everything needs_review for you to approve. Preview first with quickstart --dry-run.

Recommended agent & model

The CLI needs no model. Only the enrichment step — an agent reading code and writing accurate, source-backed docs — does, and that is where model quality matters most.

| Task | Model tier | | --- | --- | | Wiki enrichment (write/refresh docs from code) | Your agent's strongest reasoning/coding model (e.g. a Claude Opus-class model, a high-reasoning GPT-5-class model, or each tool's top coding model). Accuracy and low hallucination matter here. | | Routine upkeep (docs-sync of small changes, running validate/status) | A mid-tier or economical model is fine. | | The CLI itself (init, validate, audit, graph, stats, mcp server) | No model — pure Node, runs anywhere and in CI. |

The llm-wiki mcp server is deterministic (no model); the agent calling its tools can be any model, following the same enrichment guidance.

Core commands

| Command | What it does | | --- | --- | | quickstart --write | Set up the wiki + adapter and print the agent handoff prompt. | | validate | Structure & safety validation for local checks / CI (--strict, --changed). | | audit · status | Full findings report · current wiki state. | | graph · stats | Knowledge graph (text/JSON/Mermaid/DOT) · health snapshot. | | fix · migrate · drift | Scoped safe autofix · contract upgrade · drift downgrade (all preview-first). | | handoff · prompt | Agent handoff prompt · repeatable task prompts (feature/fix/refactor/docs-sync/okf-extract). | | mcp | Run the read-only MCP server (see below). |

Full command, option, exit-code, and programmatic-API reference: run npx llm-wiki help <command> (offline), or see PUBLIC_API.md.

Getting the most out of it

• Keep it current. Update the wiki in the same change as the code (prompt --task docs-sync), and run validate --changed in pre-commit / CI so drift is caught early.
• Trust, but verify. Agent-written docs stay needs_review; a human promotes to verified. Use drift to catch verified docs whose sources moved.
• Let agents self-serve. Point your agent at the mcp server so it queries the wiki as tools instead of re-scanning the code.
• Make it readable. graph --format mermaid, stats, and audit --format html help humans see the corpus; it renders natively on GitHub/GitLab, Obsidian, or MkDocs (it stays Markdown-in-git, not a static-site generator).
• Wire up CI. Copy templates/github-actions/llm-wiki-validate.yml to run validate on every PR, or reference the composite action in one step — uses: Dowon-Kim7949/llm-wiki-standard/.github/actions/[email protected] (pin an exact tag).

Agent-native (MCP)

llm-wiki mcp runs a Model Context Protocol server over stdio (newline-delimited JSON-RPC 2.0, Node built-ins only — no third-party SDK). Register it in an MCP client:

{ "mcpServers": { "llm-wiki": { "command": "npx", "args": ["-y", "@dowonk-7949/llm-wiki-standard", "mcp"] } } }

It exposes read-only tools — validate, audit, next, status, doctor, stats, graph, explain, handoff, prompt — so an agent can inspect the wiki but never write it. Details: PUBLIC_API.md · GATE_REVIEW.md (Gate 11).

Use it from code

Import the package instead of shelling out — handy for CI wrappers, editor integrations, and tests:

import { commands, normalizeOptions, run } from "@dowonk-7949/llm-wiki-standard";

const r = await commands.audit(normalizeOptions({ cwd: process.cwd() }));
// r.command, r.result, r.findings, r.schemaVersion

const code = await run(["validate", "--strict"]); // 0 pass / 1 error / 2 blocked / 3 usage

--format json output carries a top-level schemaVersion so wrappers can pin the contract. Full API in PUBLIC_API.md.

Safety at a glance

Preview-first everywhere (writes only with --write / --apply); verified is human-only in every command; docs/llm-wiki/log.md and existing adapter files are never overwritten; sensitive-looking values are never printed or written; no runtime third-party dependencies. Full scope decisions: GATE_REVIEW.md.

Learn more

• PUBLIC_API.md — full command / option / exit-code / configuration / programmatic-API / MCP reference.
• GATE_REVIEW.md — accepted safety scopes (fix / migrate / drift / MCP) and release gates.
• ROADMAP.md — direction and shipped history.
• EXAMPLES.md — worked examples · RELEASE_CHECKLIST.md — maintainer release steps.
• Community: CONTRIBUTING.md · CODE_OF_CONDUCT.md · SECURITY.md.