A personal knowledge base made from plain Markdown files, with original sources kept separately from the articles compiled from them. It can ingest, query, check, audit, and critique stored knowledge.

Use it to add content from URLs, files, or pasted text, ask questions about your notes, check wiki health, and review articles against their sources.

It gives you a local, readable way to keep source-backed knowledge organized and detect stale or unsupported claims.

llm-wiki — Skill for Claude Code by sammcj/agentic-coding

Install

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.

Any agent

npx skills add sammcj/agentic-coding --skill llm-wiki

Clone the repo

git clone --depth 1 https://github.com/sammcj/agentic-coding

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/sammcj/agentic-coding/llm-wiki/github.svg)](https://agentmods.dev/skills/sammcj/agentic-coding/llm-wiki)

Your own site

<a href="https://agentmods.dev/skills/sammcj/agentic-coding/llm-wiki"><img src="https://agentmods.dev/badge/skills/sammcj/agentic-coding/llm-wiki/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/sammcj/agentic-coding/llm-wiki"><img src="https://agentmods.dev/badge/skills/sammcj/agentic-coding/llm-wiki.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 82 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 5,733 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Excessive Agency · line 227
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00082	$0.05733
Opus 5.5	$0.00033	$0.02293
Sonnet 5.5	$0.00016	$0.01147
Haiku 4.5	$0.00008	$0.00573

Measured 1mo ago against content hash 21a9c144aab2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

llm-wiki 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 1mo ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/lint_mermaid.py, scripts/lint_wiki.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Skills/llm-wiki/SKILL.md · 298 lines

How it starts

The opening of the file, as written. The whole thing — 298 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LLM Wiki

A knowledge basein plain markdown. Sources land in raw/ (immutable); you compile them into wiki/ articles you own. Local markdown with YAML frontmatter, readable on GitHub, openable as an Obsidian vault. No servers, no databases, no embeddings.

Core idea (Karpathy): the LLM writes and maintains the wiki; the human chooses sources and asks questions. Knowledge is compiled once at ingest.

Invocation

Query is the default. Ingest, Lint, Audit and Critique are the four deliberate operations, each opted into by its verb or by a request that plainly calls for it. Anything else is a Query against the wiki: a bare question, "what do I know about X", "summarise everything on Y". No query keyword needed.

A leading mode argument routes straight to that operation:

ingest (alias add) - trailing text is the source: a URL, a path, or pasted content.
lint - health checks; no further input.
audit - trailing text names the article or topic to verify.
critique (alias scrutinise) - trailing text names the article, topic, or pasted content to examine.
query (alias ask) - forces query handling when a question could look like another operation.

Otherwise route natural language to Ingest, Lint, Audit or Critique only when it clearly calls for one; answer everything else as a Query.

Always required, and scenario-gated

Every operation, always:

Act only on the user's request; never background-write.
Compile any write from a source already in raw/, never straight from a live URL or an external path.
Update wiki/index.md and append wiki/log.md on any write.
Bump an article's updated whenever its content changes.
Replace outdated knowledge by superseding it, never by deleting or editing in place.

Everything else is scenario-gated. Match your task against a branch below and read that file before acting - a pointer is an instruction to open the file, not a citation. When unsure, read it: cheaper than corrupting the wiki by guessing.

Read the full file on GitHub · 298 lines

Files

What ships with it

47 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.

Changes

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.

1mo ago Changed 21a9c144aab2
1mo ago Changed · +3 lines 2bbe59f8e510
1mo ago First seen · 295 lines · 82 tokens per session scan A 0810fd5fde4e

Subscribe to this mod's changes

llm-wiki is a skill published in the GitHub repository sammcj/agentic-coding (165 stars, last pushed today), licensed Apache-2.0. It adds 82 tokens to every session and 5,733 once invoked, about $0.0003 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.

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