business/sales/apollo-sequence-load/SKILL.md
Find leads matching criteria and bulk-add them to an Apollo outreach sequence. Handles enrichment, contact creation, deduplication, and enrollment in one flow.
npx skillsauth add harsh040506/claude-code-unified-skill-plugin-library sequence-loadInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Find, enrich, and load contacts into an outreach sequence — end to end. The user provides targeting criteria and a sequence name via "$ARGUMENTS".
/apollo:sequence-load add 20 VP Sales at SaaS companies to my "Q1 Outbound" sequence/apollo:sequence-load SDR managers at fintech startups → Cold Outreach v2/apollo:sequence-load list sequences (shows all available sequences)/apollo:sequence-load directors of engineering, 500+ employees, US → Demo Follow-up/apollo:sequence-load reload 15 more leads into "Enterprise Pipeline"From "$ARGUMENTS", extract:
Targeting criteria:
person_titlesperson_senioritiesq_organization_keyword_tagsorganization_num_employees_rangesperson_locations or organization_locationsSequence info:
If the user just says "list sequences", skip to Step 2 and show all available sequences.
Use mcp__claude_ai_Apollo_MCP__apollo_emailer_campaigns_search to find the target sequence:
q_name to the sequence name from inputIf no match or multiple matches:
Use mcp__claude_ai_Apollo_MCP__apollo_email_accounts_index to list linked email accounts.
Use mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with the targeting criteria.
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.
For each approved lead:
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 personreveal_personal_emails set to trueCreate contacts — For each enriched person, use mcp__claude_ai_Apollo_MCP__apollo_contacts_create with:
first_name, last_name, email, title, organization_namedirect_phone or mobile_phone if availablerun_dedupe set to trueCollect all created contact IDs.
Use mcp__claude_ai_Apollo_MCP__apollo_emailer_campaigns_add_contact_ids with:
id: the sequence IDemailer_campaign_id: same sequence IDcontact_ids: array of created contact IDssend_email_from_email_account_id: the chosen email account IDsequence_active_in_other_campaigns: false (safe default)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 | |---|---|---|---|
Ask the user:
mcp__claude_ai_Apollo_MCP__apollo_emailer_campaigns_remove_or_stop_contact_ids to remove specific contactsstatus: "paused" and an auto_unpause_at datetesting
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.
tools
Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.
testing
This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".
development
Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO reanalysis, GSE/GSM/SRR accessions, or samplesheet creation.