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pylon_update_issue

Modify existing customer support issues in Pylon by updating status, priority, assignee, tags, visibility, or other fields to track and resolve tickets.

Instructions

Update an existing issue

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe issue ID
stateNoIssue state: new, waiting_on_you, waiting_on_customer, on_hold, closed, or custom
titleNoUpdated title
tagsNoUpdated tags
assignee_idNoNew assignee user ID
team_idNoTeam ID to assign to
account_idNoUpdated account ID
priorityNoUpdated priority
customer_portal_visibleNoWhether visible in customer portal

Implementation Reference

  • src/index.ts:348-379 (registration)
    Registers the 'pylon_update_issue' MCP tool, including input schema (zod object) and thin handler that delegates to PylonClient.updateIssue and formats response.
    server.tool(
    	'pylon_update_issue',
    	'Update an existing issue',
    	{
    		id: z.string().describe('The issue ID'),
    		state: z
    			.string()
    			.optional()
    			.describe(
    				'Issue state: new, waiting_on_you, waiting_on_customer, on_hold, closed, or custom',
    			),
    		title: z.string().optional().describe('Updated title'),
    		tags: z.array(z.string()).optional().describe('Updated tags'),
    		assignee_id: z.string().optional().describe('New assignee user ID'),
    		team_id: z.string().optional().describe('Team ID to assign to'),
    		account_id: z.string().optional().describe('Updated account ID'),
    		priority: z
    			.enum(['urgent', 'high', 'medium', 'low'])
    			.optional()
    			.describe('Updated priority'),
    		customer_portal_visible: z
    			.boolean()
    			.optional()
    			.describe('Whether visible in customer portal'),
    	},
    	async ({ id, ...data }) => {
    		const result = await client.updateIssue(id, data);
    		return {
    			content: [{ type: 'text', text: JSON.stringify(result.data, null, 2) }],
    		};
    	},
    );
  • Core implementation of issue update: performs PATCH request to Pylon API endpoint `/issues/{id}` with the provided data using the generic request method.
    async updateIssue(
    	id: string,
    	data: {
    		state?: string;
    		title?: string;
    		tags?: string[];
    		assignee_id?: string;
    		team_id?: string;
    		account_id?: string;
    		customer_portal_visible?: boolean;
    		priority?: 'urgent' | 'high' | 'medium' | 'low';
    	},
    ): Promise<SingleResponse<Issue>> {
    	return this.request<SingleResponse<Issue>>('PATCH', `/issues/${id}`, data);
    }
  • Zod schema for input validation of the pylon_update_issue tool parameters.
    {
    	id: z.string().describe('The issue ID'),
    	state: z
    		.string()
    		.optional()
    		.describe(
    			'Issue state: new, waiting_on_you, waiting_on_customer, on_hold, closed, or custom',
    		),
    	title: z.string().optional().describe('Updated title'),
    	tags: z.array(z.string()).optional().describe('Updated tags'),
    	assignee_id: z.string().optional().describe('New assignee user ID'),
    	team_id: z.string().optional().describe('Team ID to assign to'),
    	account_id: z.string().optional().describe('Updated account ID'),
    	priority: z
    		.enum(['urgent', 'high', 'medium', 'low'])
    		.optional()
    		.describe('Updated priority'),
    	customer_portal_visible: z
    		.boolean()
    		.optional()
    		.describe('Whether visible in customer portal'),
    },
  • Generic HTTP request method used by updateIssue to make authenticated API calls to Pylon.
    private async request<T>(
    	method: string,
    	path: string,
    	body?: object,
    ): Promise<T> {
    	const url = `${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?

With no annotations provided, the description carries full burden for behavioral disclosure. 'Update an existing issue' implies a mutation operation but reveals nothing about permissions required, whether updates are partial or complete, side effects (e.g., notifications), error conditions, or response format. For a mutation tool with 9 parameters, this is a significant gap in transparency.

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 appropriately sized for a straightforward update operation and front-loads the essential action. Every word earns its place.

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 (mutation tool with 9 parameters), absence of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like permissions, side effects, or response format. While the schema covers parameters well, the overall context for safe and effective use is insufficient.

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 fully documents all 9 parameters with clear descriptions and one enum. The description adds no parameter-specific information beyond what's in the schema. According to guidelines, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description.

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 issue' clearly states the verb ('Update') and resource ('an existing issue'), making the purpose immediately understandable. It distinguishes from sibling tools like pylon_create_issue (creation) and pylon_delete_issue (deletion), though it doesn't explicitly differentiate from other update tools like pylon_update_account or pylon_update_contact.

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 issue ID), when to choose this over pylon_snooze_issue or pylon_update_issue_followers, or any constraints on usage. The agent must infer usage from the tool name and schema alone.

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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