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Wiki

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AgriciDaniel
wiki

Initialize, adopt, and route work for a separate Obsidian knowledge vault through the portable claude-obsidian core. Use for vault setup, scaffolding, workspace selection, cross-project configuration, or choosing the correct wiki sub-skill. Triggers: /wiki, set up wiki, scaffold vault, create knowledge base, adopt this vault, Obsidian vault, second brain setup, persistent wiki.

Overview

PublisherAgriciDaniel
Repositoryclaude-obsidian
Skill namewiki
Stars
15K
Forks
1.5K
Bundled files
10
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 10 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by AgriciDaniel on GitHub. Read the source before you install it.

Installation

Install the Wiki AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AgriciDaniel/claude-obsidian.git /tmp/claude-obsidian
mkdir -p .claude/skills
cp -r /tmp/claude-obsidian/skills/wiki .claude/skills/wiki
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wiki in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Wiki on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Wiki is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Wiki orchestration

Treat the installed product as code and the selected user vault as data. Never use the plugin/product root as a vault, even when the current directory happens to be the product checkout.

Resolve the portable core from this skill's installation and invoke it by absolute path:

bash
CORE=/absolute/product/root/scripts/claude-obsidian.py
python3 "$CORE" --help

Resolve a vault in this order: explicit --vault, CLAUDE_OBSIDIAN_VAULT, the nearest .claude-obsidian.json, then an unambiguous initialized vault at or above the current directory. Fail closed when selection is missing or ambiguous.

Baseline setup requires no network egress. Do not fetch templates, plugins, or remote content unless the user separately approves the destinations and budget.

Set up a vault

Use the deterministic setup commands. Both are dry-run by default.

For a new, separate vault:

bash
python3 "$CORE" init /absolute/path/to/vault \
  --generated-at <ISO-UTC> --operation-id init-reviewed
python3 "$CORE" init /absolute/path/to/vault \
  --generated-at <ISO-UTC> --operation-id init-reviewed \
  --approved-plan-sha256 <reviewed-sha256> --apply

For an existing Obsidian vault:

bash
python3 "$CORE" adopt /absolute/path/to/vault \
  --generated-at <ISO-UTC> --operation-id adopt-reviewed
python3 "$CORE" adopt /absolute/path/to/vault \
  --generated-at <ISO-UTC> --operation-id adopt-reviewed \
  --approved-plan-sha256 <reviewed-sha256> --apply

Before --apply, show the selected path and changed-path preview, then pass the emitted approved_plan_sha256 unchanged. Do not use --force unless the user has reviewed the conflicts and explicitly approved replacement. Setup is non-destructive by default and creates no upstream Git remote.

If the user asks for a domain-specific scaffold, establish the baseline first, then read modes.md. Draft the additional pages and configuration as one operation-level transaction. Never mutate vault files with host Write/Edit tools or an Obsidian transport.

Route operations

Route the user's intent without silently broadening it:

IntentSkill
Ingest supplied sourceswiki-ingest
Answer from existing vault knowledgewiki-query
Save a specific conversation resultsave
Research the public web under a budgetautoresearch
Check vault healthwiki-lint
Roll up log entrieswiki-fold
Work with a canvascanvas

Query is read-only. Persistence from a query must be an explicit, separately scoped Save operation. Never capture a transcript or update the hot cache merely because a session ended.

Mutation contract

Read operation-transactions.md before any custom scaffold or mutation. One logical operation must produce one inspected and recoverable claude-obsidian.transaction.v1 bundle. Parallel agents may return drafts and evidence only; the orchestrator merges them and applies once. Every canonical page create or removal includes an active index or MOC update in that bundle; update the overview only when the stable high-level picture changed. Raw source payloads are create-only. There are no automatic commits.

Use provenance.md when initializing or changing source and claim ledgers. Unsupported evidence stays unsupported; never invent a source, quote, date, locator, or confidence.

After a successful apply, report the operation ID and exact changed paths. If the user explicitly wants a Git checkpoint, run it separately:

bash
python3 "$CORE" checkpoint OPERATION_ID --vault /absolute/path/to/vault

On a conflict, re-read and rebuild. On interruption, use transaction recover. Reuse an operation ID only with the identical bundle.

Installation context

Read install-modes.md when installation or host behavior matters. Hooks are optional adapters; portable behavior lives in the core and skills.

Conditional references

Read only the reference needed for the current request:

  • frontmatter.md when defining or adopting a property schema;
  • css-snippets.md for requested Obsidian visual customization;
  • git-setup.md for explicit local Git or checkpoint setup;
  • plugins.md when evaluating optional Obsidian integrations;
  • mcp-setup.md when the user asks to evaluate an external read transport;
  • rest-api.md only when the user explicitly has or requests the Local REST API adapter.

Think, verify, grow

Before applying, pause once: observe existing state, verify the vault selection and evidence, then choose the smallest reversible operation that satisfies the request. Afterward, report uncertainty and the next useful improvement without performing it automatically.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Wiki AI skill do?

Initialize, adopt, and route work for a separate Obsidian knowledge vault through the portable claude-obsidian core. Use for vault setup, scaffolding, workspace selection, cross-project configuration, or choosing the correct wiki sub-skill. Triggers: /wiki, set up wiki, scaffold vault, create knowledge base, adopt this vault, Obsidian vault, second brain setup, persistent wiki.

Why use Wiki on TypingMind?

Because you install it once and use it with any model. Wiki is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Wiki in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgriciDaniel/claude-obsidian/tree/main/skills/wiki. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Wiki?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Wiki?

As many as you like. As long as a model supports skills, you can use Wiki with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Wiki AI skill free?

Yes. It is published on GitHub by AgriciDaniel under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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