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draft-reply
Draft a customer support email reply based on ticket context.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
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Draft a customer support email reply based on ticket context.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | draft-reply |
| description | Draft a customer support email reply based on ticket context. |
| disable-model-invocation | true |
| argument-hint | [ticket ID] |
You are an expert customer support agent. Given a Gorgias ticket ID, analyze the full conversation and draft a professional, empathetic reply. Optionally create it as a Gmail draft.
The user's input is: $ARGUMENTS
Run composio search "get support ticket details and messages from Gorgias" "create an email draft in Gmail" in Bash.
Run composio execute <SLUG> --get-schema in Bash (in parallel) for:
GORGIAS_GET_TICKETGMAIL_CREATE_EMAIL_DRAFTRun composio execute GORGIAS_GET_TICKET -d '{"ticket_id":"<ID>"}' in Bash. If the CLI reports the toolkit is not connected, ask the user to run composio link gorgias and retry.
Parse the JSON output and extract:
Analyze the conversation to understand:
Draft a reply following these principles:
## Ticket #[ID]: [Subject]
**Customer:** [Name] <[email]>
**Status:** [status] | **Messages:** [count]
**Last customer message:** [timestamp]
### Conversation Summary
[2-3 sentence summary of the thread]
### Draft Reply
---
Subject: Re: [original subject]
[The drafted reply text]
---
### Options
1. Send as Gmail draft (will create a draft in your inbox)
2. Edit the reply (tell me what to change)
3. Regenerate with different tone (formal/casual/technical)
If the user chooses to create a Gmail draft:
composio execute GMAIL_CREATE_EMAIL_DRAFT -d '{"to":"<customer email>","subject":"Re: <original subject>","body":"<approved draft text>"}' in BashAutomatically analyze and tag untagged [Gorgias](https://composio.dev/toolkits/gorgias) tickets based on content.
Extract a structured bug report from a support ticket and create a [Linear](https://composio.dev/toolkits/linear) issue.
Summarize customer support/sales calls from [Dialpad](https://composio.dev/toolkits/dialpad) or [Leexi](https://composio.dev/toolkits/leexi) call logs
Review and improve AI chatbot responses using conversation logs from [Botsonic](https://composio.dev/toolkits/botsonic), [Docsbot](https://composio.dev/toolkits/docsbot-ai), or [Landbot](https://composio.dev/toolkits/landbot)
Sync customer data between [Gorgias](https://composio.dev/toolkits/gorgias) and [HubSpot](https://composio.dev/toolkits/hubspot) - find mismatches and missing contacts
Send CSAT follow-up emails to customers after ticket resolution via [Gmail](https://composio.dev/toolkits/gmail)