How Obsidian Skills Work with AI Agents: A Declarative Interface for Vault Automation

Obsidian Skills enable AI agents to read, write, and manipulate Obsidian vaults through declarative SKILL.md files that define Markdown formats, CLI commands, and data schemas without requiring executable code.

The kepano/obsidian-skills repository implements the open Agent Skills specification, allowing compatible AI systems like Claude Code, Codex CLI, and OpenCode to understand Obsidian-specific data structures and perform vault operations using natural language prompts.

The Agent Skills Architecture

The integration relies on a declarative architecture where skills are defined as documentation rather than code. This makes them portable across any environment that implements the Agent Skills specification.

Skill Definitions in SKILL.md Files

Each skill resides under skills/<skill-name>/SKILL.md and contains a YAML front-matter block plus human-readable documentation. The front-matter specifies the skill name, description, and input/output formats, while the body details workflows and syntax patterns.

For example, skills/obsidian-markdown/SKILL.md defines how agents should generate frontmatter, wikilinks, and callouts. Similarly, skills/obsidian-cli/SKILL.md documents the command syntax for vault mutations.

Runtime Discovery and Registration

Agent-Skills compatible runtimes auto-discover these definitions. OpenCode automatically finds all SKILL.md files in the workspace, while Claude Code expects them in the /.claude/ directory. The runtime registers each skill's name and description, making it available for the LLM to invoke via natural language requests.

The Execution Layer

When a skill requires vault mutation, the obsidian-cli skill translates LLM intent into CLI calls. The obsidian command line interface communicates with a running Obsidian instance through its built-in HTTP bridge, enabling agents to create notes, read files, search content, and execute plugin commands directly.

How AI Agents Process Obsidian Commands

When you ask an agent to perform a vault operation, the system follows a five-step execution loop:

1. Prompt Detection — The LLM recognizes Obsidian-specific keywords like "create a note," "add a tag," or "show the task table."
2. Skill Lookup — The runtime matches the request to a registered skill name, such as obsidian-markdown for content creation or obsidian-cli for file system operations.
3. Payload Creation — Using the skill's "Workflow" description, the model generates the required Markdown structure, CLI parameters, or YAML configuration.
4. Invocation — The runtime either returns the generated text (for display or confirmation) or executes the obsidian CLI command on the user's machine.
5. Feedback Loop — The agent can read back the created file or vault state to confirm success and continue with subsequent operations.

Core Data Formats Supported

The skill system supports three primary Obsidian data structures that agents can generate and manipulate:

• Markdown — Standard .md files with Obsidian extensions including wikilinks ([[...]]), embeds, and callouts (> [!warning]).
• Bases — .base YAML files that describe filtered database views, formulas, and property configurations.
• JSON Canvas — .canvas files describing visual node graphs for diagramming and whiteboarding.

Practical Implementation Examples

The following examples demonstrate how agents translate natural language requests into structured outputs using specific skills.

Generating Structured Notes with obsidian-markdown

When prompted to create a project note with specific Obsidian features, the agent uses the obsidian-markdown skill to generate proper frontmatter and syntax:

User: "Create a project note for 'Alpha' with a wikilink to the roadmap and a warning callout."

Agent generates:

---
title: Alpha Project
date: 2024-10-01
tags:
  - project
  - alpha
aliases:
  - Alpha
---

# Alpha Project

This project aims to [[Improve workflow]] by Q4.

> [!warning] Deadline Alert
> All milestones must be completed by **2024‑12‑31**.

The skill's workflow section (lines 12-17 of skills/obsidian-markdown/SKILL.md) instructs the LLM to include YAML frontmatter, use double-bracket wikilink syntax, and format callouts with the > [!type] convention.

Vault Mutation via obsidian-cli

To actually write the note to the vault, the agent switches to the obsidian-cli skill and generates a shell command:

obsidian create name="Alpha Project" \
               content="---
title: Alpha Project
date: 2024-10-01
tags:
  - project
  - alpha
---

# Alpha Project

This project aims to [[Improve workflow]] by Q4.

> [!warning] Deadline Alert
> All milestones must be completed by **2024‑12‑31**." \
               silent overwrite

This follows the syntax documented in skills/obsidian-cli/SKILL.md, where the create command accepts name, content, and optional flags like silent and overwrite.

Querying Data with obsidian-bases

For database-style operations, the obsidian-bases skill generates .base YAML files that define filtered views:

filters:
  and:
    - file.hasTag("todo")
    - 'status != "done"'
formulas:
  days_until_due: 'if(due, (date(due) - today()).days, "")'
properties:
  status:
    displayName: Status
  formula.days_until_due:
    displayName: "Days Until Due"
views:
  - type: table
    name: "Open Tasks"
    order:
      - formula.days_until_due
      - file.name
      - status

The "Schema" and "Default Summary Formulas" sections (lines 17-63 of skills/obsidian-bases/SKILL.md) guide the model in constructing valid filter expressions and formula syntax.

Summary

• Obsidian Skills are declarative definitions stored in skills/<name>/SKILL.md files that teach AI agents how to work with Obsidian-specific formats.
• The system supports Claude Code, OpenCode, and other Agent Skills-compatible runtimes that auto-discover these definitions.
• Three primary formats are supported: Markdown (with wikilinks and callouts), Bases (filtered YAML databases), and JSON Canvas (visual diagrams).
• The obsidian-cli skill provides the execution layer, translating LLM commands into HTTP calls to a running Obsidian instance.
• No executable code resides in the skill repository—only documentation—making skills portable and safe across different AI environments.

Frequently Asked Questions

What AI agents are compatible with Obsidian Skills?

Any agent implementing the Agent Skills specification can use these definitions, including Claude Code, Codex CLI, and OpenCode. Each runtime auto-discovers SKILL.md files in the workspace (or in /.claude/ for Claude Code) and registers the described capabilities for natural language invocation.

Do I need to install software to use Obsidian Skills with an AI agent?

You need the Obsidian CLI installed and running to enable write operations, as the obsidian-cli skill depends on this tool to communicate with Obsidian via its HTTP bridge. However, the skills themselves require no installation—they are simply Markdown documentation files that the agent reads to understand Obsidian's data formats.

How do Obsidian Skills differ from Obsidian plugins?

Obsidian Skills are declarative documentation that teach AI agents how to generate valid Obsidian content, while plugins are executable code that run inside Obsidian. Skills contain no logic; they rely on the host agent's LLM to interpret the documentation and generate proper syntax. This makes skills portable across any AI environment without security risks or version conflicts.

Can I create custom skills for my specific vault workflows?

Yes. Following the Agent Skills specification, you can create a SKILL.md file in a skills/<your-skill-name>/ directory that defines custom templates, metadata schemas, or CLI workflows specific to your vault structure. Place it where your AI agent's runtime can discover it (typically the workspace root or /.claude/), and the agent will incorporate your custom definitions into its available tool set.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}