get_design_guideClueso's house style for composing video clips — how to think about concept, typography, color, composition, motion, and pacing. Read it before composing or editing a clip's visuals when you're NOT following a clueprint, or to fill gaps a clueprint leaves silent. General craft, not clueprint-specific.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / properties / contextRemoved value: -{
- "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
- "type": "string"
-}Input schema / properties / conversation_idRemoved value: -{
- "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
- "type": "string"
-}Input schema / properties / llm_modelRemoved value: -{
- "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
- "type": "string"
-}Input schema / requiredRemoved value: -[
- "context",
- "llm_model"
-]Input schema / properties / contextAdded value: +{
+ "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+ "type": "string"
+}Input schema / properties / conversation_idAdded value: +{
+ "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+ "type": "string"
+}Input schema / properties / llm_modelAdded value: +{
+ "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+ "type": "string"
+}Input schema / requiredAdded value: +[
+ "context",
+ "llm_model"
+]Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds no additional behavioral traits (e.g., output format or length of the guide), but since it's a simple read operation, this is acceptable and matches the calibration for read-only tools.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, with the core purpose stated first, followed by usage guidance. There is no wasted language, and every phrase adds value, making it efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters, no output schema, and simple annotations, the description is complete. It tells the agent exactly what the guide covers, when to use it, and how it relates to clueprints, leaving no ambiguity about when to call this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is no schema to add meaning. The baseline is 4, and the description does not need to explain any parameters; it correctly focuses on when to use the guide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides Clueso's house style for video composition, covering specific aspects like concept, typography, color, composition, motion, and pacing. This is a specific resource (design guide) with a clear purpose, distinct from any sibling tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool: before composing or editing a clip's visuals when NOT following a clueprint, or to fill gaps a clueprint leaves silent. It also explicitly says the guide is general craft, not clueprint-specific, so agents know when it's not the right tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.