1 email reported from 1 company, first seen , last seen . Praises a repository you own, then pitches a tool.
Template
From
{sender_name} at agentrq.com
Template
Reconstructed from 1 copy
Hi {recipient_first_name},
Saw how {recipient_repo} {compliment_detail}. Building AgentRQ, an open-source control plane for AI agents with scheduled tasks and routines via a dual-mode MCP architecture.
Worth a look on GitHub?
-
{sender_name}, intern agent @ AgentRQ
Contextual, Inc.
Gentle note: This is a one-time email to get your optional opinion. If you don't want to get further communication emails, just reply unsubscribe to this email back. We do not store any information about you, and this email will be deleted in 7 days if there is no reply.
What goes in the slots
{recipient_first_name}
Recipient's first name.
{recipient_repo}
Name of the recipient's repository.
{compliment_detail}
A specific repository behavior or feature to praise.Seen: “auto-refreshes every 6 hours”
{sender_name}
Name of the person signing the email.
>_The likely prompt
Low confidence, 38%
Write a concise, personalized cold outreach email using these inputs: recipient first name {recipient_first_name}, repository name {recipient_repo}, notable repository behavior {compliment_detail}, and sender name {sender_name}. Open with “Hi” and the recipient's first name. Mention the repository behavior as a brief compliment, then pitch AgentRQ using this description: “an open-source control plane for AI agents with scheduled tasks and routines via a dual-mode MCP architecture.” Ask whether the recipient would take a look on GitHub. Sign off as “{sender_name}, intern agent @ AgentRQ,” then include the Contextual, Inc. attribution and the exact gentle note provided in the template. Keep the tone casual, direct, and lightly personalized; do not add unsupported claims or extra paragraphs. Use the subject “Automating discovery pipelines.”
Reconstructed from the copies below. The sender’s real prompt may differ.
Hi {recipient_first_name},
Saw how {recipient_repo} auto-refreshes every 6 hours. Building AgentRQ, an open-source control plane for AI agents with scheduled tasks and routines via a dual-mode MCP architecture.
Worth a look on GitHub?
-
{sender_name}, intern agent @ AgentRQ
Contextual, Inc.
Gentle note: This is a one-time email to get your optional opinion. If you don't want to get further communication emails, just reply unsubscribe to this email back. We do not store any information about you, and this email will be deleted in 7 days if there is no reply.