sequence-load

anthropics/knowledge-work-plugins · updated Apr 8, 2026

$npx skills add https://github.com/anthropics/knowledge-work-plugins --skill sequence-load
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summary

Find, enrich, and load contacts into an outreach sequence — end to end. The user provides targeting criteria and a sequence name via "$ARGUMENTS".

skill.md

Sequence Load

Find, enrich, and load contacts into an outreach sequence — end to end. The user provides targeting criteria and a sequence name via "$ARGUMENTS".

Examples

  • /apollo:sequence-load add 20 VP Sales at SaaS companies to my "Q1 Outbound" sequence
  • /apollo:sequence-load SDR managers at fintech startups → Cold Outreach v2
  • /apollo:sequence-load list sequences (shows all available sequences)
  • /apollo:sequence-load directors of engineering, 500+ employees, US → Demo Follow-up
  • /apollo:sequence-load reload 15 more leads into "Enterprise Pipeline"

Step 1 — Parse Input

From "$ARGUMENTS", extract:

Targeting criteria:

  • Job titles → person_titles
  • Seniority levels → person_seniorities
  • Industry keywords → q_organization_keyword_tags
  • Company size → organization_num_employees_ranges
  • Locations → person_locations or organization_locations

Sequence info:

  • Sequence name (text after "to", "into", or "→")
  • Volume — how many contacts to add (default: 10 if not specified)

If the user just says "list sequences", skip to Step 2 and show all available sequences.

Step 2 — Find the Sequence

Use mcp__claude_ai_Apollo_MCP__apollo_emailer_campaigns_search to find the target sequence:

  • Set q_name to the sequence name from input

If no match or multiple matches:

  • Show all available sequences in a table: | Name | ID | Status |
  • Ask the user to pick one

Step 3 — Get Email Account

Use mcp__claude_ai_Apollo_MCP__apollo_email_accounts_index to list linked email accounts.

  • If one account → use automatically
  • If multiple → show them and ask which to send from

Step 4 — Find Matching People

Use mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with the targeting criteria.

  • Set per_page to the requested volume (or 10 by default)

Present the candidates in a preview table:

# Name Title Company Location

Ask: "Add these [N] contacts to [Sequence Name]? This will consume [N] Apollo credits for enrichment."

Wait for confirmation before proceeding.

Step 5 — Enrich and Create Contacts

For each approved lead:

  1. Enrich — Use mcp__claude_ai_Apollo_MCP__apollo_people_bulk_match (batch up to 10 per call) with:

    • first_name, last_name, domain for each person
    • reveal_personal_emails set to true
  2. Create contacts — For each enriched person, use mcp__claude_ai_Apollo_MCP__apollo_contacts_create with:

    • first_name, last_name, email, title, organization_name
    • direct_phone or mobile_phone if available
    • run_dedupe set to true

Collect all created contact IDs.

Step 6 — Add to Sequence

Use mcp__claude_ai_Apollo_MCP__apollo_emailer_campaigns_add_contact_ids with:

  • id: the sequence ID
  • emailer_campaign_id: same sequence ID
  • contact_ids: array of created contact IDs
  • send_email_from_email_account_id: the chosen email account ID
  • sequence_active_in_other_campaigns: false (safe default)

Step 7 — Confirm Enrollment

Show a summary:


Sequence loaded successfully

Field Value
Sequence [Name]
Contacts added [count]
Sending from [email address]
Credits used [count]

Contacts enrolled:

Name Title Company Email

Step 8 — Offer Next Actions

Ask the user:

  1. Load more — Find and add another batch of leads
  2. Review sequence — Show sequence details and all enrolled contacts
  3. Remove a contact — Use mcp__claude_ai_Apollo_MCP__apollo_emailer_campaigns_remove_or_stop_contact_ids to remove specific contacts
  4. Pause a contact — Re-add with status: "paused" and an auto_unpause_at date

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.651 reviews
  • Ganesh Mohane· Dec 28, 2024

    sequence-load has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Dec 24, 2024

    Registry listing for sequence-load matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Michael Diallo· Dec 24, 2024

    sequence-load has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • James Bhatia· Dec 12, 2024

    sequence-load fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sakura Jain· Dec 4, 2024

    Keeps context tight: sequence-load is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Ava Taylor· Dec 4, 2024

    Registry listing for sequence-load matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Camila Liu· Nov 23, 2024

    Useful defaults in sequence-load — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • James Chawla· Nov 23, 2024

    I recommend sequence-load for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Kofi Johnson· Nov 23, 2024

    sequence-load reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Yash Thakker· Nov 15, 2024

    sequence-load reduced setup friction for our internal harness; good balance of opinion and flexibility.

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