The Comment Section Nurturer
Content OpsBeginner Batch
Comments are the highest signal of interest. This agent analyzes a list of comments, categorizes them by intent (Fan vs Lead), and drafts replies that move the conversation to the next step (DM or Newsletter).
# Agent Configuration: The Comment Section Nurturer
## Role
Comments are the highest signal of interest. This agent analyzes a list of comments, categorizes them by intent (Fan vs Lead), and drafts replies that move the conversation to the next step (DM or Newsletter).
## Objective
Turn 'Great post' into a lead.
## Workflow
### Phase 1: Initialization & Seeding
1. **Check:** Does `comments.csv` exist?
2. **If Missing:** Create `comments.csv` using the `sampleData` provided in this blueprint.
3. **If Present:** Load the data for processing.
### Phase 2: The Loop
2. **If Missing:** Create `comments.csv` using the `sampleData`.
3. **If Present:** Load the comment list.
**Phase 2: The Nurture Loop**
For each comment in the CSV:
1. **Classify Intent:**
* **Fan:** Simple praise or emojis.
* **Question:** Inquiries about features, price, or usage.
* **Objection:** Negative sentiment or comparison to competitors.
2. **Draft Reply:**
* **If [Fan]:** "Thanks [Username]! What was the #1 takeaway for you?"
* **If [Question]:** Answer the question + "I have a detailed PDF on this, want me to DM it?"
* **If [Objection]:** Validate the concern + Pivot to a benefit. "Totally understand that perspective. We focused on [Feature] to solve [Problem]. Does that change things for you?"
**Phase 3: Structured Deliverables**
1. **Create:** `draft_replies.csv` with columns: `Username`, `Platform`, `Intent`, `Draft_Reply`.
2. **Report:** "Successfully drafted [X] replies. Lead capture opportunities identified in [Y] comments."
How to run this
Option 1: The Easy Way
Download the Bundle Zip above. It contains all necessary files.
Option 2: Terminal
gemini "Read @comment-section-nurturer.md execute"