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recipe_list

Skills / Recipes · macOS · Windows

Effect: read (strongest supported action). Status: gated.

Gated means the tool requires an installed app, a connected account, permission, or runtime availability. Check those requirements on the listed platform before using it.

macOS

Purpose

Lists the user's reusable SKILLS — saved recipes (an ordered sequence of LMCP tool calls with parameters), plus bundled ones — each runnable with recipe_run. Skills turn a repeated LMCP workflow into one reusable command. A user would list them to find an existing skill for a task rather than rebuilding it from scratch. Returns each skill's name, description, and steps.

Required inputs

No required inputs are declared in this platform's schema. Optional selectors and runtime requirements may still apply.

Permissions and confirmation

No explicit confirmation parameter is exposed in this snapshot. This does not grant permission to act: obtain user authorization before any real action.

Full input schema — macOS
{
  "properties": {},
  "required": [],
  "type": "object"
}

Documentation example

Do not execute this example. These concrete inputs refer to a fictional demonstration dataset. Resolve real handles and obtain user authorization before any real call.

{}

Windows

Purpose

Lists the user's reusable SKILLS — saved recipes (an ordered sequence of LMCP tool calls with parameters), each runnable with recipe_run. A user would list them to find an existing skill for a task rather than rebuilding it from scratch. Returns each recipe's name, description, and step count.

Required inputs

No required inputs are declared in this platform's schema. Optional selectors and runtime requirements may still apply.

Permissions and confirmation

No explicit confirmation parameter is exposed in this snapshot. This does not grant permission to act: obtain user authorization before any real action.

Full input schema — Windows
{
  "properties": {},
  "required": [],
  "type": "object"
}

Documentation example

Do not execute this example. These concrete inputs refer to a fictional demonstration dataset. Resolve real handles and obtain user authorization before any real call.

{}