From GTM Skills
Finds qualified prospects and decision-makers using multi-source public research, role mapping, and source confidence. Use when building target lists or finding buyers at named accounts.
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/gtm-skills:lead-findingThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
The most common lead-finding mistake is relying on a single source — usually a B2B database like Apollo or ZoomInfo — and accepting whatever it returns as the universe of addressable accounts. Single-source lead discovery produces lists with systematic gaps: entire categories of companies that don't appear in one database but dominate another. The non-obvious rule is that high-quality lead disc...
The most common lead-finding mistake is relying on a single source — usually a B2B database like Apollo or ZoomInfo — and accepting whatever it returns as the universe of addressable accounts. Single-source lead discovery produces lists with systematic gaps: entire categories of companies that don't appear in one database but dominate another. The non-obvious rule is that high-quality lead discovery requires multiple, complementary sources, each with its own coverage bias, used in combination to triangulate the full universe of ICP-matching companies.
This skill provides a multi-source lead discovery methodology spanning eight source categories: B2B contact databases (Apollo, Sales Navigator), professional networks (LinkedIn Sales Navigator advanced search), code repositories and technical communities (GitHub, Stack Overflow, DevPost), funding and company databases (Crunchbase, PitchBook, Tracxn), job boards (LinkedIn Jobs, Indeed, Wellfound), conference and event lists (event sponsor/exhibitor lists, speaker rosters), industry directories and associations, and vertical-specific sources (G2/Capterra for SaaS, BuiltWith for technographics, SaaStr/Product Hunt for early-stage).
For each source, the skill provides search templates, data extraction patterns, and guidance on which sources are most productive for specific verticals (SaaS, fintech, healthcare, manufacturing, e-commerce, professional services). The output is a deduplicated, prioritized lead list with source provenance, ready for enrichment and scoring.
Do NOT use for:
Winning by Design — SPICED Framework. The Situation component maps to lead sourcing: finding companies in the right "situation" (industry, size, stage) that is the starting point for SPICED qualification. The Decision component maps to identifying the right contacts within sourced companies.
Force Management — MEDDICC. The Economic Buyer, Champion, and Decision Process elements guide which contacts to find within sourced companies. Finding a company is not enough — you need to find the specific personas who can champion, influence, and authorize a purchase.
Gartner — Buying Committee Research. The finding that B2B buying committees average 6-10 decision makers informs the contact discovery strategy. Finding one contact at a company is insufficient — the skill targets identification of 2-4 key personas per account.
ColdIQ / Alex Hoar — Multi-Source Prospecting. The methodology of combining Sales Navigator, job boards, funding data, and conference lists to build comprehensive prospect lists rather than relying on a single database.
Ask all questions at once:
Source Prioritization by Vertical: Different verticals have different source strengths. Prioritize sources based on the target industry:
SaaS / Technology:
Fintech / Financial Services:
Healthcare / HealthTech:
Manufacturing / Industrial:
E-commerce / Retail:
Professional Services:
Execute multi-source discovery following this sequence:
Step 1: B2B Database Export (Apollo or equivalent)
If you have Apollo access:
Apollo search template per persona:
Step 2: LinkedIn Sales Navigator Advanced Search
Sales Navigator provides company and people search with filters not available in regular LinkedIn:
Company search template:
People search template per persona:
Export results using Sales Navigator's list-building feature. Note: LinkedIn terms of service prohibit automated scraping. Use native export features only.
Step 3: GitHub and Technical Communities (for technical ICPs)
For companies where technology stack matters:
topic:kubernetes org:, search for companies by their GitHub org pages)Step 4: Crunchbase and Funding Databases
For growth-stage and funded companies:
Step 5: Job Boards
Hiring signals are strong ICP indicators. Search:
Search for roles that indicate the company needs your product:
Step 6: Conference and Event Lists
Conference sponsor, exhibitor, and speaker lists are high-quality sources:
Step 7: Industry Directories and Associations
Step 8: Vertical-Specific Sources
Step 9: Deduplication and Merge
After collecting from all sources:
Step 10: Initial Prioritization
Apply a lightweight prioritization before full enrichment:
Deliver a structured lead list with:
Also deliver a Source Performance Summary showing how many unique companies each source contributed (accounting for overlap) and recommendations for which sources to prioritize in future lead-finding cycles.
# Lead Discovery Report: [Company Name]
## Discovery Summary
- Total unique companies discovered: [#]
- Sources used: [#]
- Date range: [Start - End]
## Source Performance
| Source | Companies Found | Unique to This Source | Overlap % |
|--------|----------------|----------------------|-----------|
| Apollo | [#] | [#] | [%] |
| Sales Navigator | [#] | [#] | [%] |
| Crunchbase | [#] | [#] | [%] |
| Job Boards | [#] | [#] | [%] |
| Conferences | [#] | [#] | [%] |
| GitHub | [#] | [#] | [%] |
| [Other] | [#] | [#] | [%] |
---
## Lead List
| # | Company | Domain | Industry | Size | Location | Sources | Contacts | Tier |
|---|---------|--------|----------|------|----------|---------|----------|------|
| 1 | [Name] | [.com] | [Ind] | [# emp] | [City, ST] | [3 sources] | [2 contacts] | 1 |
| 2 | [Name] | [.com] | [Ind] | [# emp] | [City, ST] | [2 sources] | [1 contact] | 2 |
[Full lead list — recommend CSV export for large lists]
---
## Source-Specific Exports
### Apollo Results ([#] companies)
[Summary table]
### Sales Navigator Results ([#] companies)
[Summary table]
### Crunchbase Results ([#] companies)
[Summary table]
### [Additional sources]
---
## Recommendations
- Best sources for future cycles: [Ranked list based on unique contribution, quality, and cost]
- Sources to deprioritize: [Low-unique-contribution sources]
- Coverage gaps: [ICP segments not well represented in discovered leads]
- Next step: Run lead-enrichment on Tier 1 and Tier 2 leads
Before delivering, verify:
Single-source dependency. Relying on Apollo or ZoomInfo alone produces systematic coverage gaps. Apollo underrepresents non-US, non-funded, and traditional-industry companies. Sales Navigator underrepresents very small companies. Crunchbase only covers funded companies. Multi-source is not optional — it's the difference between seeing 60% of your addressable market and seeing 90%+.
Using the same search criteria across all sources. Each source has its own taxonomy and filters. "Manufacturing" in Apollo is not the same as "Manufacturing" in Sales Navigator. Adapt search criteria to each source's specific categorization system. Test and calibrate.
Finding companies but not contacts. A list of companies without contacts is a research artifact, not a prospecting list. Every company in the lead list should have at least contact count and, for Tier 1 leads, specific contact names and titles. Use the persona definitions from ICP to guide contact discovery.
Accepting database coverage as reality. If Apollo returns 500 companies matching your ICP in the US, there are almost certainly more than 500. The database return count is a lower bound, not the actual market size. Use the coverage gaps section to identify where additional sources might surface more leads.
Skipping source provenance tracking. When a lead turns out to be high-quality (or low-quality), knowing which source it came from is essential for optimizing future lead-finding cycles. Without provenance data, you can't improve your sourcing strategy.
Prioritizing volume over quality. A list of 5,000 poorly-matched leads is less valuable than 500 precisely-matched leads. Apply ICP criteria aggressively during discovery, not after. It's better to surface fewer, better-matched companies than to dump everything into enrichment.
Neglecting vertical-specific sources. The B2B databases cover broad markets well but specific verticals poorly. Healthcare companies are better found through hospital directories than Apollo. E-commerce companies are better found through BuiltWith. Always include at least one vertical-specific source.
Job board scraping that produces stale data. Job postings expire. Conference lists age out. Source data has a half-life. Track the date of data collection per source and flag leads from sources where the data is more than 90 days old for re-verification.
references/framework-notes.md — Named frameworks and reference tablestemplates/output-template.md — Deliverable shell for agent outputscripts/check-output.py — Lightweight deliverable validatorgtm-context: Run before this skill. Provides the ICP definition that drives search criteria.
icp-scoring: Run before this skill. Provides the scoring model to prioritize discovered leads.
lead-enrichment: Run after this skill. Takes the discovered lead list and enriches each company and contact with additional data.
signal-scoring: Run after this skill. Scores discovered leads on dynamic signals (hiring, funding, tech stack, intent) to identify active buyers.
list-building: Run after lead-enrichment. Builds production-ready prospecting lists in Clay with enrichment and verification.
email-finding: Run after lead-enrichment. Discovers email addresses for the contacts found during lead discovery.
npx claudepluginhub leadmagic/gtm-skillsBuilds qualified prospect lists for B2B SaaS, general B2B, local SMBs, or early-stage demand-signal discovery using ICP fit, growth signals, and public pain signals.
Builds qualified prospect lists for B2B SaaS, general B2B, or local small businesses. Covers ICP definition, lead sourcing, verification, and scoring.
Finds, enriches, and qualifies prospects against library ICP criteria, using segments, personas, and Motion cells. Useful for outbound lead generation.