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read_ai_skill

Read a bundled skill by ID from the skills list to give AI assistants structured Unity workflow or agent guidance without requiring the Unity Editor.

Instructions

Read a bundled skill by id from list_ai_skills (e.g. unity-scenes-workflow, unity-runtime-performance).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "skill_id": "<skill_id>"
    },
    "name": "read_ai_skill"
  }
}

Input Schema

NameRequiredDescriptionDefault
skill_idYesSkill folder id, e.g. unity-scenes-workflow or unity-ml-agents

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.2

TDQS

A3.7/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. "Bundled" usefully signals the content is packaged locally rather than fetched live, and "Read" implies a non-mutating operation, but there is no disclosure of what is returned, how large skill bodies are, or what happens with an unknown skill_id.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence with the action and the id source front-loaded and examples placed parenthetically at the end. Nothing could be removed without losing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read tool with no output schema, the description covers the essential calling contract: what to pass and where valid values come from. The main remaining gap is the shape of the returned content, which matters more here than for a typical lookup.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and only one parameter exists, so the schema already documents skill_id with its own examples. The description reinforces this with additional concrete id examples (unity-scenes-workflow, unity-runtime-performance) and makes explicit that ids originate from list_ai_skills, which the schema does not say.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Read a bundled skill by id") and ties it to the discovery tool list_ai_skills, so an agent can tell it apart from the lister. It stops short of saying what a "skill" actually contains (instructions, docs, config), so the resource is named but not characterized.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase "by id from list_ai_skills" implies the prerequisite flow: enumerate ids first, then read one. There is no explicit when-not-to-use guidance and no mention of read_agent_docs, a sibling that also retrieves documentation-like content and could plausibly be confused with this one.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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