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validate_color

Check if a color string is valid for LIFX smart lights before applying it to ensure proper lighting control.

Instructions

Validate a color string

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYesLIFX API token
colorYesColor string to validate

Implementation Reference

  • The handler executes the validate_color tool by sending the color string to the LIFX /color API endpoint for validation and parsing, then returns the parsed result.
    case "validate_color": {
      const { token, color } = args as { token: string; color: string };
      const result = await makeLIFXRequest(`/color?color=${encodeURIComponent(color)}`, { token });
    
      return {
        content: [
          {
            type: "text",
            text: `Color validation result:\n${JSON.stringify(result, null, 2)}`,
          },
        ],
      };
    }
  • src/index.ts:248-259 (registration)
    Registration of the validate_color tool, including its name, description, and input schema definition.
    {
      name: "validate_color",
      description: "Validate a color string",
      inputSchema: {
        type: "object",
        properties: {
          token: { type: "string", description: "LIFX API token" },
          color: { type: "string", description: "Color string to validate" },
        },
        required: ["token", "color"],
      },
    },
  • Input schema defining the parameters for the validate_color tool: LIFX token and color string.
    inputSchema: {
      type: "object",
      properties: {
        token: { type: "string", description: "LIFX API token" },
        color: { type: "string", description: "Color string to validate" },
      },
      required: ["token", "color"],
    },
  • Shared helper function used by all tools, including validate_color, to make authenticated HTTP requests to the LIFX API.
    async function makeLIFXRequest(
      endpoint: string,
      options: {
        method?: string;
        body?: any;
        token: string;
      }
    ): Promise<any> {
      const { method = "GET", body, token } = options;
      
      const url = `${LIFX_API_BASE}${endpoint}`;
      const headers: Record<string, string> = {
        "Authorization": `Bearer ${token}`,
        "User-Agent": USER_AGENT,
      };
    
      if (body && (method === "POST" || method === "PUT")) {
        headers["Content-Type"] = "application/json";
      }
    
      try {
        const response = await fetch(url, {
          method,
          headers,
          body: body ? JSON.stringify(body) : undefined,
        });
    
        if (!response.ok) {
          const errorText = await response.text();
          throw new Error(`LIFX API error: ${response.status} ${response.statusText} - ${errorText}`);
        }
    
        // Some endpoints return empty responses
        const contentType = response.headers.get("content-type");
        if (contentType?.includes("application/json")) {
          return await response.json();
        }
        
        return await response.text();
      } catch (error) {
        throw new Error(`Failed to make LIFX API request: ${error instanceof Error ? error.message : String(error)}`);
      }
    }
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It doesn't disclose what validation entails (e.g., format checking, API verification), error handling, rate limits, or authentication requirements. The mention of 'color string' hints at input format but lacks depth.

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?

The description is a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for a simple validation tool, making it easy to parse quickly.

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

Completeness2/5

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

For a tool with no annotations, no output schema, and two required parameters (including an API token), the description is inadequate. It doesn't explain the validation logic, return values, error cases, or how it integrates with sibling tools, leaving significant gaps for an agent.

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

Parameters3/5

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

Schema description coverage is 100%, so parameters are documented in the schema. The description adds no additional meaning beyond implying 'color' is the string to validate, which the schema already states. Baseline 3 is appropriate as the schema does the heavy lifting.

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?

The description clearly states the action ('validate') and the target ('a color string'), making the purpose immediately understandable. It doesn't distinguish from siblings like 'set_state' or 'breathe_effect', but the verb+resource combination is specific enough for basic understanding.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites like needing a valid token, nor does it explain why validation might be needed before using other color-related tools like 'set_state' or 'breathe_effect'.

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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