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pylon_update_tag

Modify existing tags in the Pylon customer support platform by updating their names and colors to organize and categorize support data effectively.

Instructions

Update an existing tag

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe tag ID
valueNoUpdated tag name
hex_colorNoUpdated hex color

Implementation Reference

  • src/index.ts:551-565 (registration)
    Registers the MCP tool 'pylon_update_tag' with input schema (id required, value/hex_color optional) and a handler that delegates to PylonClient.updateTag and returns JSON response.
    server.tool(
    	'pylon_update_tag',
    	'Update an existing tag',
    	{
    		id: z.string().describe('The tag ID'),
    		value: z.string().optional().describe('Updated tag name'),
    		hex_color: z.string().optional().describe('Updated hex color'),
    	},
    	async ({ id, ...data }) => {
    		const result = await client.updateTag(id, data);
    		return {
    			content: [{ type: 'text', text: JSON.stringify(result.data, null, 2) }],
    		};
    	},
    );
  • Zod input schema for the tool parameters.
    {
    	id: z.string().describe('The tag ID'),
    	value: z.string().optional().describe('Updated tag name'),
    	hex_color: z.string().optional().describe('Updated hex color'),
    },
  • Thin MCP tool handler that invokes PylonClient.updateTag.
    async ({ id, ...data }) => {
    	const result = await client.updateTag(id, data);
    	return {
    		content: [{ type: 'text', text: JSON.stringify(result.data, null, 2) }],
    	};
    },
  • Core handler implementing the tag update by making a PATCH request to the Pylon API /tags/{id} endpoint.
    async updateTag(
    	id: string,
    	data: { value?: string; hex_color?: string },
    ): Promise<SingleResponse<Tag>> {
    	return this.request<SingleResponse<Tag>>('PATCH', `/tags/${id}`, data);
    }
  • Shared HTTP request helper method used by updateTag to perform the API call.
    private async request<T>(
    	method: string,
    	path: string,
    	body?: object,
    ): Promise<T> {
    	const url = `${PYLON_API_BASE}${path}`;
    	const headers: Record<string, string> = {
    		Authorization: `Bearer ${this.apiToken}`,
    		'Content-Type': 'application/json',
    		Accept: 'application/json',
    	};
    
    	const response = await fetch(url, {
    		method,
    		headers,
    		body: body ? JSON.stringify(body) : undefined,
    	});
    
    	if (!response.ok) {
    		const errorText = await response.text();
    		throw new Error(
    			`Pylon API error: ${response.status} ${response.statusText} - ${errorText}`,
    		);
    	}
    
    	return response.json() as Promise<T>;
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Update an existing tag' implies a mutation operation, but it doesn't disclose critical behavioral traits: whether this requires specific permissions, if it's idempotent, what happens on invalid inputs (e.g., duplicate tag names), or error handling. For a mutation tool with zero annotation coverage, this is a significant gap.

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 wasted words. It's front-loaded with the core action ('Update an existing tag'), making it immediately scannable and appropriately sized for its purpose.

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?

Given the complexity (a mutation tool with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like permissions, idempotency, or error handling, nor does it explain the update's effect (e.g., whether it modifies all fields or only provided ones). For a tool that changes data, this leaves critical gaps.

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 the schema already documents all three parameters (id, value, hex_color) with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain parameter relationships, constraints, or examples. Baseline 3 is appropriate when 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 'Update an existing tag' clearly states the verb ('update') and resource ('tag'), making the purpose immediately understandable. It distinguishes this from sibling tools like pylon_create_tag (creation) and pylon_delete_tag (deletion), though it doesn't explicitly mention what aspects of the tag are updated (name/color).

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 (e.g., needing an existing tag ID), when not to use it (e.g., for creation vs. update), or how it differs from similar update tools like pylon_update_account or pylon_update_contact. Usage is implied but not explicitly stated.

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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