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Parallel Lead Qualification with ICP Evidence

Qualify lead CSVs with parallel research, evidence for each ICP criterion, and reliable pass, fail, or review decisions.

Saleslead-qualificationicp
by AgentVoltv1.0.0
Free to sign up · every skill included with AgentVolt Pro

Before & after

Same prompt, same agent — the only difference is the skill.

Prompt“Qualify 150 sales leads against our ideal customer profile in one batch.”
Beforegeneric AI agent
I can help you research and qualify those leads. I'd go through them and check whether they match your criteria. It would probably take a while to do all 150 at once, but I could work through them systematically. I'd need to know what your ideal customer profile looks like so I can evaluate each one. How detailed do you want the qualification to be? We could do a quick pass or dig deeper into each lead. Should I just give you a yes or no, or would you like explanations too?
Afterwith Parallel Lead Qualification with ICP Evidence
BATCH QUALIFICATION SETUP

Input CSV: leads.csv (150 rows)
ICP Criteria: B2B SaaS, ARR > 5M, has sales team
Batch size: 10 leads per sub-agent
Parallel agents: 15 (handles 150 in parallel)
Method: Web search verification per lead
Runtime: ~2 minutes

OUTPUT CSV - QUALIFIED LEADS

Lead ID | Company | Qualification | Reason | Score
---
4521 | Acme Corp | QUALIFIED | SaaS, 8M ARR, 25-person team | 9.2
4522 | Beta Inc | QUALIFIED | B2B software, 6.2M ARR, GTM team | 8.7
4523 | Gamma Ltd | NOT_QUALIFIED | Consulting firm (services, not SaaS) | 2.1
4524 | Delta AI | QUALIFIED | AI automation platform, 5.8M ARR | 8.9
... (146 more rows)

SUMMARY STATS

Qualified: 82 leads (54.7%)
Not qualified: 68 leads (45.3%)
Disposition breakdown:
  - Perfect fit (score 8+): 34
  - Good fit (score 6-7): 48
  - Poor fit: 68

NEXT ACTION

Export qualified list to CRM
Schedule outreach sequence starting tomorrow
Expected conversion: 18-24 meetings

About this skill

Your lead list looks relevant, but company names, directory categories, and guessed locations do not prove ICP fit. This skill divides the research across available sub-agents, applies one qualification policy, and returns a CSV with evidence behind every decision. Unclear leads stay marked for review instead of becoming false positives.

What it does

  • Converts an ICP into mandatory criteria, exclusions, and precise evidence requirements before research begins.
  • Resolves the correct company and domain so similarly named businesses do not get mixed together.
  • Assigns disjoint batches to available sub-agents with bounded research effort and compact result returns.
  • Separates confirmed matches, confirmed failures, and unresolved criteria using PASS, FAIL, and NEEDS_REVIEW.
  • Preserves original CSV values and row order while adding reasons, source URLs, and criterion evidence.
  • Reconciles returned rows, checks inconsistent decisions, and reports qualification counts and unresolved work.

What you get

An annotated lead CSV and a brief reconciliation report showing who qualifies, why others fail, and which leads need another look. Each decision includes criterion-level evidence and sources; unavailable research or execution capabilities are stated plainly.

Best for

Sales operations and outbound teams checking sizable lead lists against requirements such as services offered, headquarters location, business type, and company size before enrichment or outreach.

SKILL.md preview

SKILL.md
---
name: parallel-lead-qualification-with-icp-evidence
description: >-
  Qualify leads against an ICP with criterion-level evidence by splitting a lead CSV into batches and dispatching parallel sub-agents to qualify each batch. Use when the user says "qualify this lead CSV", "split lead research across agents", "check these companies against our ICP", "add a qualified column", "filter these prospects without guessing", or "rank these leads by ICP fit".
---

# Parallel Lead Qualification with ICP Evidence

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