Best use case
Instantly Autoreply is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
## Purpose
Teams using Instantly Autoreply should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/instantly-autoreply/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Instantly Autoreply Compares
| Feature / Agent | Instantly Autoreply | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
## Purpose
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Instantly Autoreply ## Purpose Automatically generate and send intelligent replies to incoming emails from Instantly campaigns, using campaign-specific knowledge bases and web research. ## Inputs The webhook receives this payload from Instantly (reply event): - `timestamp`: ISO timestamp when the event occurred - `event_type`: Type of event (e.g., "reply") - `campaign_id`: UUID of the campaign - `campaign_name`: Name of the campaign (format: "CAMPAIGN_ID | Campaign Name") - `lead_email`: The prospect's email address - `email_account`: The sending account (eaccount) - `email_id`: UUID of the email to reply to (use as reply_to_uuid) - `reply_subject`: Subject line of the incoming reply - `reply_text`: Full plain text content of the incoming reply - `reply_html`: Full HTML content of the incoming reply - `reply_text_snippet`: Short preview of the reply content - Additional lead data fields may be present ## Process ### Step 1: Parse Incoming Reply The incoming email content is already in the payload: - `reply_text` or `reply_html`: The full content of their reply - `reply_subject`: Their subject line Use this directly - no need to fetch. ### Step 2: Get Full Conversation History (Optional) If more context is needed, call `instantly_get_emails` with the lead_email to retrieve prior emails (limit 10). ### Step 3: Extract Campaign ID Parse the campaign_name to get the ID (everything before the "|"). Or use `campaign_id` directly if available. ### Step 4: Lookup Knowledge Base Call `read_sheet` on spreadsheet `1QS7MYDm6RUTzzTWoMfX-0G9NzT5EoE2KiCE7iR1DBLM` to find the row where column "ID" matches the campaign ID. Extract: - `Knowledge Base`: Campaign-specific context and talking points - `Reply Examples`: Example replies to match tone ### Step 5: Skip if No Knowledge Base If no knowledge base found for this campaign, skip processing and return empty. ### Step 6: Generate Reply Using extended thinking, generate a reply following these rules: **Role & Tone:** - Write as the email_account (first person: 'I', 'we') - Concise, confident, friendly, non-corporate, outcome-focused - No em dashes (—), no over-explaining, no hype, no filler - If followup: be light but persistent, illustrate value props **Research (use web_search tool):** - Research the sender and their company/clinic thoroughly - Look up any products, tools, locations, acronyms you don't recognize - Use research to tailor the reply (don't mention you searched) **When to Return Empty (no reply):** - If additional email would be needless (they confirmed call, logistics done) - If explicitly negative: "DO NOT EMAIL", "UNSUBSCRIBE", "remove me from list" - If no knowledge base found **Output Format:** - 3-8 sentences unless thread requires more - HTML with `<br>` for line breaks, `<br><br>` between paragraphs - No `<html>`, `<body>`, `<p>` tags - Sign off with first name from email_account ### Step 7: Filter Empty Replies If the generated reply is empty or just whitespace, do NOT send. Return success with `skipped: true`. ### Step 8: Send Reply Call `instantly_send_reply` with: - `eaccount`: The email_account from input - `reply_to_uuid`: The email_id from input - `subject`: The reply_subject from input - `html_body`: The generated reply ## Output Return: - `status`: "success" or "error" - `skipped`: true if reply was intentionally empty - `reply_sent`: true if reply was actually sent - `message_id`: ID from Instantly if sent ## Error Handling - If Instantly API fails: Log error, return error status - If knowledge base lookup fails: Skip this email (no KB = no reply) - If AI generation fails: Log error, do not send partial reply ## Knowledge Base Sheet Structure Spreadsheet ID: `1QS7MYDm6RUTzzTWoMfX-0G9NzT5EoE2KiCE7iR1DBLM` | ID | Campaign Name | Knowledge Base | Reply Examples | |----|---------------|----------------|----------------| | abc123 | Dental Outreach | [context...] | [examples...] |
Related Skills
Instantly Automation
Automate Instantly cold email outreach -- manage campaigns, sending accounts, lead lists, bulk lead imports, and campaign analytics -- using natural language through the Composio MCP integration.
Daily Logs
Record the user's daily activities, progress, decisions, and learnings in a structured, chronological format.
Socratic Method: The Dialectic Engine
This skill transforms Claude into a Socratic agent — a cognitive partner who guides
Sokratische Methode: Die Dialektik-Maschine
Dieser Skill verwandelt Claude in einen sokratischen Agenten — einen kognitiven Partner, der Nutzende durch systematisches Fragen zur Wissensentdeckung führt, anstatt direkt zu instruieren.
College Football Data (CFB)
Before writing queries, consult `references/api-reference.md` for endpoints, conference IDs, team IDs, and data shapes.
College Basketball Data (CBB)
Before writing queries, consult `references/api-reference.md` for endpoints, conference IDs, team IDs, and data shapes.
Betting Analysis
Before writing queries, consult `references/api-reference.md` for odds formats, command parameters, and key concepts.
Research Proposal Generator
Generate high-quality academic research proposals for PhD applications following Nature Reviews-style academic writing conventions.
Paper Slide Deck Generator
Transform academic papers and content into professional slide deck images with automatic figure extraction.
Medical Imaging AI Literature Review Skill
Write comprehensive literature reviews following a systematic 7-phase workflow.
Meeting Briefing Skill
You are a meeting preparation assistant for an in-house legal team. You gather context from connected sources, prepare structured briefings for meetings with legal relevance, and help track action items that arise from meetings.
Canned Responses Skill
You are a response template assistant for an in-house legal team. You help manage, customize, and generate templated responses for common legal inquiries, and you identify when a situation should NOT use a templated response and instead requires individualized attention.