Post Engagement Prospector

Instructions

When a user wants to find prospects from LinkedIn post engagement, run this workflow: extract commenters and reactors, filter by ICP, enrich, and create a list.

Steps

Step 1: Gather input from the user

Ask for:

• The LinkedIn post URL (required)
• Whether to pull comments, reactions, or both
• ICP filter criteria: target titles, seniority levels, industries, or company sizes to keep
• Whether to exclude certain profiles (e.g. "exclude people who already replied to our outreach")
• List name (or generate one from the post context)

Step 2: Pull post engagement

If the user wants commenters, call mcp__claude_ai_toflow__get_linkedin_post_comments with the post URL.

If the user wants reactors, call mcp__claude_ai_toflow__get_linkedin_post_reactions with the post URL.

Combine both lists if the user wants all engagement. Deduplicate by LinkedIn URL.

Step 3: Filter by ICP

Review the returned profiles against the user's ICP criteria. Filter out:

• Profiles whose titles or companies do not match the target
• Profiles with incomplete data
• Any explicit exclusions the user specified

Present a summary: "Found X commenters and Y reactors. Z match your ICP criteria."

Step 4: Enrich each matching profile

For each matching LinkedIn URL, call mcp__claude_ai_toflow__enrich_person_by_linkedin to pull their full profile: job title, company, email, phone, and contact details.

For large lists (20+ people), use mcp__claude_ai_toflow__add_people_to_list first to create the list, then call mcp__claude_ai_toflow__bulk_enrich_list to enrich all at once. Show the credit estimate first using estimate_bulk_enrich_list.

Step 5: Create the list

Call mcp__claude_ai_toflow__create_list with a descriptive name (e.g. "Post Engagers - [Post Topic] - Jun 2026"). Call mcp__claude_ai_toflow__add_people_to_list with the LinkedIn URLs of matching profiles.

Step 6: Surface personalization context

For each contact, note the specific signal: did they comment or react? If they commented, include a snippet of their comment. This becomes the personalization hook for outreach.

Step 7: Confirm and summarize

Report the list name, total contacts added, enrichment status, and a few example personalization hooks.

Important Notes

• Post engagement data is time-sensitive. Note when the post was published and flag if it is older than 30 days.
• Always apply ICP filtering before enriching. Enriching everyone from a large post wastes credits.
• The comment text is a high-value personalization signal. Preserve it in your output so reps can reference it in outreach.
• If the same person commented and reacted, count them once and note both signals.

Examples

Example 1: Build list from competitor announcement

User: "This post is from a competitor. Pull everyone who commented and is a VP of Sales or above at a SaaS company."

1. Calls get_linkedin_post_comments with the URL.
2. Filters returned profiles: keeps VP, SVP, EVP, C-Suite titles at SaaS companies.
3. Reports: "23 people commented. 11 match your ICP."
4. Calls create_list named "Competitor Post Commenters - Jun 2026".
5. Calls add_people_to_list with 11 LinkedIn URLs.
6. Calls estimate_bulk_enrich_list, shows cost.
7. Calls bulk_enrich_list after approval.
8. Returns list with enrichment status and comment snippets for each contact.

Example 2: Pull reactions from industry report

User: "Get everyone who reacted to this industry report post. Filter for Director and above in marketing or RevOps."

1. Calls get_linkedin_post_reactions.
2. Filters for Director+ in Marketing and Revenue Operations.
3. Creates list, enriches, surfaces reaction as personalization signal.

Troubleshooting