Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Oshayr/LLM-Wiki --skill servegit clone --depth 1 https://github.com/Oshayr/LLM-WikiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/oshayr/llm-wiki/serve)<a href="https://agentmods.dev/skills/oshayr/llm-wiki/serve"><img src="https://agentmods.dev/badge/skills/oshayr/llm-wiki/serve/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/oshayr/llm-wiki/serve"><img src="https://agentmods.dev/badge/skills/oshayr/llm-wiki/serve.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.00551 |
| Opus 5.5 | $0.00019 | $0.00220 |
| Sonnet 5.5 | $0.00010 | $0.00110 |
| Haiku 4.5 | $0.00005 | $0.00055 |
Grade A, and why
wiki-serve scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wiki Serve
Launch a local web server that presents the wiki as a browsable, Wikipedia-style website with live background research, integrated chat, and a split-pane editor with AI assist.
Resolve .wiki/ from plugin install scope. Auto-create if missing.
Arguments
/wiki-serve— start the server (default port 8420)/wiki-serve stop— stop the running server
Startup
The FastAPI web server only runs when explicitly requested. There are two ways to start it:
Skill-Based Launch
- Run the
/wiki-serveskill from Claude Code (recommended):/wiki-serve - The server automatically:
- Installs dependencies if needed
- Handles page indexing, research workers, and file watching
- Opens your browser to localhost:8420
Manual Launch
Dependencies are installed automatically by the plugin's SessionStart hook. To start the server manually from the command line:
python path/to/skills/serve/scripts/server.py --wiki-dir .wiki/ --port 8420
Replace path/to with the full path to your LLM-Wiki installation (typically .claude/plugins/llm-wiki).
If dependencies are missing, install manually: pip install -r requirements.txt
Features
- Page rendering — markdown → HTML with wiki-link transformation, red-link detection
- Live research — click any red link to trigger background research (stub-first: summary in 30s, full upgrade async)
- Search — full-text search with autocomplete
- Split-pane editor — markdown + live preview, markdown toolbar, AI assist bar
- Page type templates — concept, brainstorming, idea, memory, status, rules, config, skill, plus custom templates from
.wiki/templates/ - Chat — wiki-aware AI assistant in bottom-right panel
- Research queue — manage, cancel, reorder research tasks
- Knowledge graph — interactive page relationship visualization
- Three themes — light, dark, terminal
- Export — HTML and markdown download
Stop
Kill the server process on port 8420. Either:
/wiki-serve stop- The server auto-stops when the session ends (daemon process)
What ships with it
29 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/architecture.md 24 KB
- scripts/__init__.py 29 B runs code
- scripts/chat_manager.py 14 KB runs code
- scripts/markdown_renderer.py 17 KB runs code
- scripts/rag_handler.py 3.2 KB runs code
- scripts/research_queue.py 20 KB runs code
- scripts/research_worker.py 26 KB runs code
- scripts/server.py 67 KB runs code
- scripts/wiki_store.py 32 KB runs code
- static/chat.js 12 KB runs code
- static/editor.js 9.4 KB runs code
- static/style.css 70 KB
- static/wiki.js 29 KB runs code
- templates/base.html 9.2 KB
- templates/canvas.html 5.1 KB
- templates/create.html 13 KB
- templates/edit.html 3.5 KB
- templates/error.html 432 B
- templates/gaps.html 6.1 KB
- templates/graph.html 12 KB
- templates/history.html 4.1 KB
- templates/home.html 4.6 KB
- templates/page.html 8.3 KB
- templates/recent.html 1.1 KB
- templates/research_dashboard.html 5.7 KB
- templates/researching.html 5.3 KB
- templates/review.html 4.6 KB
- templates/search.html 2.6 KB
- templates/stats.html 2.7 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 62 lines · 48 tokens per session scan A edaa2563662b
wiki-serve is a skill published in the GitHub repository Oshayr/LLM-Wiki (50 stars, last pushed 6mo ago), licensed MIT. It adds 48 tokens to every session and 551 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
llm-wiki
Build and maintain an LLM-curated knowledge base from papers, articles, transcripts, notes and project findings. Ingest sources into linked Markdown, answer questions with citations, lint or upgrade a wiki, and preserve useful synthesis across sessions and agents. Also capture verified task experience, consolidate…
webapp-testing
To test local web applications, write native Python Playwright scripts.
verify-feature
Auto-detect changed frontend routes, navigate them with Playwright, take screenshots, and check for console/network errors. Use after implementing a frontend feature to verify it works visually — auto-detects routes from git changes or accepts a route argument. Supports --responsive for mobile testing and…
screenshot
Capture a screenshot of a URL or route with one command. Use whenever the user wants to take a screenshot, capture a page, see what a route looks like, or visually verify a page. Supports mobile viewport with --mobile and unauthenticated mode with --no-auth.
mcp-tools
When and how to use the bundled and optional MCP tools — context7 library docs, Playwright browser automation, Mermaid diagram validation, and GitHub (gh CLI first). Apply when looking up library APIs, verifying frontend pages in a browser, validating diagrams, or doing GitHub operations.
smoke-test
Smoke test the running frontend and API by navigating key routes with Playwright, checking for console errors and broken pages. Use after starting the dev server or to verify the app works before creating a PR.