Generated banner for Prospecting
Generated logo for Prospecting

Prospecting

Corey HainesCommunityCreated by Corey Haines

  • Skill
  • Workflow
  • Business and productivity
  • MIT
  • No issues found

From the author

When the user wants to find, qualify, and build a list of prospects to reach out to, across B2B SaaS, general B2B, or local small businesses. Also use when the user mentions "prospecting," "build a prospect list," "find leads," "lead list," "outbound list," "target account list," "ICP-fit accounts," "find local businesses," "find my first customers," "design partners," "signal-based outbound," "gap plays," "buying signals," "intent data," "job change alerts," "waterfall enrichment," "Clay table," "lookalike accounts," "catch-all emails," "account tiering," or "research this account before I reach out." Always verify emails before they reach a sequence, and never scrape LinkedIn. Define audiences in Sales Navigator and pull contacts from licensed data. Covers list building, signals, enrichment, verification, and account research. For the outreach itself (copy, sending setup, LinkedIn, cadences, replies), see cold-email. For researching competitors, see competitor-profiling.
— the description by Corey Haines

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a systematic approach to building lead lists by defining an Ideal Customer Profile (ICP) and applying branch-specific discovery methods. It covers four distinct motions: B2B SaaS, general B2B, local SMBs, and early-stage demand-signal discovery. The process emphasizes data verification, compliance with communication regulations, and the use of licensed data sources to ensure lead quality. It guides users through defining ICPs, sourcing candidates, qualifying leads against specific signals, and prioritizing accounts for outreach.

What it does

  • Defines ICPs based on firmographic, technographic, and behavioral signals.
  • Builds candidate lists using licensed data sources and browser-assisted research.
  • Verifies email deliverability to maintain outreach reputation.
  • Scores and tiers prospects based on buying signals and ICP fit.
  • Generates lead sheets in markdown tables or CSV format.
  • Ensures compliance with GDPR, CAN-SPAM, and platform terms of service.

When to use it

  • When you need to build a targeted list of prospects for outbound outreach.
  • When you need to identify early-stage customers or design partners via public signals.
  • When you need to qualify leads based on specific trigger events or buying signals.
  • When you need to research accounts to create personalized outreach briefs.

Advantages

  • Provides a consistent, repeatable framework for lead generation.
  • Reduces bounce rates through mandatory email verification.
  • Maintains compliance by tracking source lineage for every contact.
  • Prevents account suspension by prohibiting bulk scraping of platforms.

Usage examples

“Build a list of 25 B2B SaaS companies that recently raised a Series A and are hiring for growth roles.”
The agent will define the ICP, source companies using tools like Apollo or Crunchbase, verify contact emails, and output a scored table of leads.
“Find 15 local dental clinics in Austin, Texas, that have an active website.”
The agent will use browser-assisted research to identify clinics, verify their website status, and provide a list with contact information and confidence scores.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/coreyhaines31/prospecting/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip prospecting.zip -d .agents/skills

Documentation by Corey Haines

Prospecting

You are an expert at building qualified prospect lists across four motions: B2B SaaS, general B2B, local small businesses, and early-stage demand-signal discovery (finding your first customers from public pain signals). Your goal is to turn an ICP definition into a verified, scored, ready-to-outreach lead sheet — using the right data sources, qualification signals, and compliance posture for each motion.

Before Starting

Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Pick the Branch

Prospecting motions differ enough that the workflow forks at intake. Pick one branch based on who the user is selling to:

BranchSell toWhat "qualified" looks likePrimary sources
SaaSOther SaaS companies / digital businessesICP fit + tech stack match + growth signals (funding, hiring, product velocity)LinkedIn, BuiltWith, Crunchbase, Apollo, Clay, ProductHunt
B2BNon-SaaS B2B (services, manufacturers, enterprises, mid-market)Industry + size + geographic fit + buying signals (trigger events, vendor changes)Apollo, ZoomInfo, Clay, LinkedIn Sales Nav, industry directories
Local SMBLocal small businesses (shops, gyms, restaurants, clinics, salons, services)Active business + website status + proximity + decision-maker accessGoogle Maps, Yelp, local directories, Facebook, business websites
Demand-signalEarly-stage: your first customers, design partners, or beta usersEvidence of the exact pain/demand/timing signal — a cited public source, not just firmographic fitForums, communities, reviews, GitHub issues, job posts, launch announcements (via last30days, social-fetch, scraping)

If the user describes a hybrid motion (e.g., "SMBs that are also SaaS"), pick the dominant branch and pull in qualification signals from the other. If the user is early-stage and needs their first customers or design partners — evidence of demand over list coverage — use the Demand-signal branch.

For the branch-specific deep dives:


Shared Framework (all branches)

Every prospecting engagement follows the same five phases. Tools and qualification signals change per branch; the phases don't.

Phase 1 — Define the ICP

Pull from product-marketing.md if available. Otherwise, gather:

  1. Firmographic fit — industry, company size, revenue band, geography, business model

  2. Technographic fit (SaaS branch) — what tools they already use, what they're missing

  3. Buying signal — why now? (trigger event, funding, hiring, new initiative, dissatisfaction with current vendor, recent move/expansion)

  4. Decision-maker profile — role, seniority, what they care about

  5. Disqualifiers — what makes a prospect a clear "skip"

Output the ICP as a one-paragraph statement plus a checklist of pass/fail criteria. Don't move to discovery without this.

Phase 2 — Build the candidate list (discovery)

Source 2–3× more candidates than the user wants in the final list — qualification will cull aggressively.

  • SaaS / B2B: combine 2–3 sources for cross-verification. Apollo or ZoomInfo for firmographics; Clay or a waterfall aggregator (FullEnrich, LeadMagic) for enrichment; LinkedIn Sales Nav for decision-maker mapping.

  • Local SMB: browser-assisted research starting with Google Maps for the target category in the target area; cross-check with Yelp, the business website, social pages, and public directories.

If the user's list quality bar is high, smaller is better. 25 verified leads beats 250 mostly-junk ones.

For LinkedIn audiences, define the filters in Sales Navigator and pull the contacts from a licensed database. For legitimate non-LinkedIn sources, AI list builders, lookalikes, and the enrichment waterfall, see references/sourcing-and-enrichment.md. To find accounts by what just happened to them (hiring, job changes, product usage, funding), gap plays (a signal plus a gap you can verify from outside, such as ads running with no visible tracking), or warm paths through your own network, see references/signal-plays.md.

Phase 3 — Qualify each candidate

Score every candidate against the ICP checklist. Add evidence (a source URL or two) for each qualification — never assert without backing.

Confidence levels (used across all branches):

  • High: confirmed by at least two independent sources or official business page

  • Medium: one credible source plus consistent search evidence

  • Low: incomplete or ambiguous evidence — flag what remains uncertain

For email contacts (B2B / SaaS branches), always verify deliverability before adding to the final list, and again within 7 days of sending if the list sat. Catch-all domains need a set policy. See references/sourcing-and-enrichment.md for the verification actions, catch-all handling, and the suppression list. Don't ship leads with invalid or risky emails.

Phase 4 — Score and prioritize

Apply this rubric for the SaaS, B2B, and Local SMB branches. The Demand-signal branch scores differently — 0–100 demand-fit, not Hot/Warm/Cold — see references/demand-signals.md.

ScoreDefinition
HotStrong ICP fit + clear buying signal + decision-maker accessible + verified contact
WarmICP fit + softer or older signal + contact verifiable
ColdLoose ICP fit OR no clear signal OR contact unverified
SkipDisqualifier hit (out of ICP, closed business, duplicate, irrelevant, low confidence)

Branch-specific signals refine the scoring — see each reference file. Default ratio target: ~20% Hot, ~30% Warm, rest Cold/Skip.

Then assign an account tier, which sets how much research and how many channels each account gets: Tier 1 (1:1, the top 25–50), Tier 2 (1:few, segments of 20–200 sharing one pain), Tier 3 (1:many). Tier 1 accounts get a sourced research brief before any outreach. See references/signal-plays.md for tiers and references/account-research.md for the brief and the rules for agent research.

Phase 5 — Output the lead sheet

(SaaS / B2B / Local SMB. The Demand-signal branch ships an evidence report instead — see references/demand-signals.md.)

Default to a markdown table in chat. Switch to CSV when the list is >25 rows or the user explicitly asks for a file.

After the table, always add "Top outreach targets" — the top 3–5 hot leads with one sentence each on why this lead should be reached out to first.

Columns vary by branch (see reference files), but every lead sheet includes:

  • score, business/company name, contact (where applicable), why-it's-a-prospect, source(s), confidence, last verified date


Compliance Guardrails

These apply to every branch. Read first, every engagement.

  1. No bulk scraping of LinkedIn, Google Maps, paywalled sites, or rate-limited APIs. Browser is an assisted research tool, not a scraper.

  2. No CAPTCHA, login wall, or bot protection bypass. If a site requires it, work with what's publicly visible.

  3. Public business contact channels only. Use info@, hello@, contact@, and named-role emails (founder, owner) where they're published on the business's own site. Personal/private emails require a lawful basis (existing relationship, opt-in, etc.).

  4. GDPR / CAN-SPAM / CASL aware. Capture and retain the source URL and date for every contact you add to a list — required for downstream outreach compliance.

  5. No reselling extracted data from Google Maps, LinkedIn, or any platform whose terms prohibit it. List building for the user's own outreach is fine; productizing the list to sell is not.

  6. Rate limit yourself. Even on public sources, space requests. Don't fingerprint as a bot.

  7. No breached, leaked, or unprovenanced data. Don't source prospects from breached datasets, scraped-contact marketplaces, or list brokers with no source lineage. Licensed B2B data providers (Apollo, ZoomInfo, Clay, and similar) are fine when used within their ToS and with a lawful basis — the ban is on illicit/unprovenanced data, not on legitimate enrichment vendors.

  8. Never target or infer sensitive traits. Don't qualify, segment, or personalize on health, financial hardship, political belief, sexuality, religion, or other protected/sensitive attributes — even when a public post reveals them.

For the full compliance reference (GDPR, CAN-SPAM, CASL, LinkedIn ToS, Google Maps ToS, Clay/Apollo/ZoomInfo use restrictions): see references/compliance.md.


Inputs to Collect

If missing, ask once, then infer reasonable defaults and continue:

  • Branch (SaaS / B2B / Local SMB / Demand-signal) — usually inferable from context; pick Demand-signal for early-stage first-customer discovery

  • ICP description — pull from product-marketing.md if present

  • Target count — default 25 for SaaS / B2B, 15 for Local SMB

  • Geography (essential for Local SMB; useful for B2B; less critical for SaaS)

  • Tools the user has access to — Apollo? Clay? ZoomInfo? Hunter? Truelist? Defaults to what's free + browser

  • Output format — chat table (default) or CSV

  • Buying signal preference — what triggers should they prioritize? (funding rounds, hiring, recent move, etc.)


Enrichment Workflows

For multi-provider lookups, cache reuse, and per-credit budgets, load the enrichment playbook. Define accepted results first, stop the waterfall when satisfied, and keep lookup errors distinct from no-match records.


Tool Selection Quick Picks

Full breakdown in references/data-sources.md. Quick picks:

If the user has access to...Use it for
ApolloB2B / SaaS firmographic + contact discovery
ClayMulti-source enrichment, waterfall lookups, custom scoring
FullEnrich or LeadMagicWaterfall email and phone enrichment through one API
TheirStackHiring signals and tech stacks from job posts
ZoomInfoEnterprise B2B contact + intent data
Hunter or SnovEmail pattern guessing and verification
TruelistEmail deliverability validation (before adding to outreach list)
LinkedIn Sales NavigatorDecision-maker mapping (manual, no scraping)
BuiltWith / WappalyzerTech stack qualification (SaaS branch)
CrunchbaseFunding signals (SaaS branch)
GitHubStargazers / forks of competitor or adjacent repos (dev-tool SaaS branch)
Google Maps + browserLocal SMB discovery
Firecrawl / BrowserbaseProgrammatic extraction from individual prospect websites — never from platforms

If the user has no enrichment tools: lean on browser-assisted research with public sources — company website, About page, LinkedIn company page, news mentions. Slower but works.


Output Formats

Default — chat table

For SaaS / B2B (≤25 rows):

| Score | Company | Industry | Size | Signal | Contact | Email status | Source | Confidence |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |

For Local SMB (≤15 rows) — port from the local-prospector reference:

| Score | Business | Category | Area | Website status | Website/Social | Phone | Why it's a prospect | Confidence |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
CSV — when >25 rows or user requests a file

SaaS / B2B columns:

score,company,domain,industry,size_band,country,signal,contact_name,contact_title,contact_email,email_status,linkedin,source_urls,why_prospect,confidence,verified_date,notes

Local SMB columns:

score,business,category,area,distance_km,website_status,website_url,social_urls,phone,email,source_urls,why_prospect,confidence,verified_date,notes
Always include after the table
  • Top outreach targets: top 3–5 hot leads with one-sentence outreach rationale each

  • Search parameters: branch, ICP, location/radius, target count, date generated

  • Open questions: anything you couldn't verify and the user should look at


Quality Checks (before finalizing)

  • [ ] Remove duplicates (by domain for SaaS/B2B, by business + address for Local SMB)

  • [ ] Every "Hot" lead has a verified contact + at least one source URL

  • [ ] No lead has an email that failed Truelist (or your validator) verification — move to a separate "invalid" bucket and flag for the user

  • [ ] No lead labeled "Hot" lacks a clear buying signal

  • [ ] Confidence levels honest — "High" requires 2 independent sources, not just two of your own searches

  • [ ] No leads sourced from prohibited scraping (LinkedIn at scale, Google Maps bulk extract, etc.)

  • [ ] Source URL + date captured for every contact (GDPR / CAN-SPAM lineage)

  • [ ] Final count matches user's request, or you've explained why it's smaller (quality bar)


Common Mistakes

  1. Starting discovery without an ICP. Build candidates against vague criteria and you'll qualify the wrong things.

  2. Treating data sources as authoritative without cross-checks. Apollo and ZoomInfo are out of date often; verify before scoring as "Hot."

  3. Adding contacts without email verification. Cold email reputation tanks fast with bounces — always validate.

  4. Bulk scraping LinkedIn or Google Maps. Real risk: account suspension + ToS violation. Browser as an assisted tool only.

  5. Mixing branches. Don't apply Local SMB scoring (website status) to a B2B SaaS prospect, or vice versa.

  6. "Hot" labels without buying signals. ICP fit alone is not enough — the signal is what makes the timing right.

  7. No source URLs. Every claim should be traceable to a public source. Future outreach depends on this lineage.

  8. Ignoring quiet hours / time zone when scheduling the downstream outreach (handoff to cold-email).

  9. Forgetting to retain consent / lineage records. Required for GDPR DSARs and CAN-SPAM audits.


Task-Specific Questions

  1. Which branch — SaaS, B2B, Local SMB, or Demand-signal (early-stage, finding your first customers)?

  2. What's your ICP? (Or: should I pull from your product-marketing context?)

  3. How many qualified leads do you want?

  4. What tools do you have access to (Apollo / Clay / ZoomInfo / Hunter / Truelist / browser only)?

  5. What's the triggering buying signal you care most about?

  6. Geography or radius (Local SMB / B2B)?

  7. Chat table or CSV?


Tool Integrations

For implementation, see the tools registry. Key prospecting tools:

ToolBest ForMCPGuide
ApolloB2B / SaaS firmographic + contact discovery✓apollo.md
ClayMulti-source enrichment + waterfall✓clay.md
FullEnrichWaterfall email + phone enrichment✓fullenrich.md
LeadMagicEmail, phone, and job-change enrichment✓leadmagic.md
TheirStackHiring signals and tech stacks from job posts✓theirstack.md
ApifyStructured data from public directories (never LinkedIn)✓apify.md
ZoomInfoEnterprise B2B contact + intent✓zoominfo.md
HunterEmail pattern + verification✓hunter.md
SnovEmail finder + verifier-snov.md
TruelistEmail verification, including catch-all resolution✓truelist.md
OutreachSales engagement (post-list)✓outreach.md
RB2BVisitor identification (warm intent)-rb2b.md
Ploy ◆Visitor identification on Ploy-hosted sites (one option alongside RB2B and other visitor-ID tools)-ploy.md
GitHubStargazers/forks/watchers as developer-intent signal-github.md
FirecrawlSingle-target site extraction (prospect's own website)✓firecrawl.md
BrowserbaseReal-browser site research when rendering or interaction needed✓browserbase.md

  • cold-email: For writing outbound sequences against the qualified list (the natural next step after prospecting)

  • customer-research: For understanding why current customers buy — informs the ICP definition

  • competitor-profiling: For researching competitors. Research on accounts you're selling to lives here, in references/account-research.md

  • revops: For lead routing, lifecycle, and CRM handoff after prospecting

  • sales-enablement: For battle cards and one-pagers used in the outreach

  • directory-submissions: For inbound discovery surfaces (the prospects might find you back)

  • product-marketing: For the ICP definition that anchors every prospecting engagement

Files

references/data-sources.md

Prospecting Data Sources

Tool selection guide for prospecting across all three branches.


Tool selection by goal

GoalPrimary toolsNotes
Build initial firmographic list (B2B / SaaS)Apollo, ZoomInfo, ClayApollo for breadth, ZoomInfo for enterprise + intent, Clay for custom workflows
Decision-maker mappingLinkedIn Sales Navigator (manual), Apollo, ZoomInfoSales Nav is the gold standard. Never bulk scrape it.
Tech stack qualification (SaaS)BuiltWith, WappalyzerBuiltWith has wider coverage + paid plans for bulk; Wappalyzer is lighter + free for small use
Funding signals (SaaS)Crunchbase, PitchbookCrunchbase free tier sufficient for early signals; Pitchbook for deeper investor data
Email pattern discoveryHunter, Snov, ApolloPattern guessing — followed by verification
Email deliverability verificationTruelist, Hunter, NeverBounce, ZeroBounceAlways verify before adding to outreach lists
Visitor identification (warm intent)RB2B, Warmly, Vector, Ploy ◆ (sites hosted on Ploy)Anonymous traffic → company or person identification
Intent dataZoomInfo Intent, 6sense, BomboraPre-warmed signals; mid-market+ pricing
Trigger event monitoringGoogle Alerts, Feedly, LinkedIn Sales Nav alertsFree options are sufficient for most
Local business discoveryGoogle Maps (manual), Yelp, Facebook PagesBrowser-assisted, not bulk-extracted

Apollo

Use for: General B2B / SaaS firmographic + contact data. Best starting point if you don't already have a list.

Strengths:

  • Large database (>200M contacts, >60M companies)

  • Strong filtering UI (industry, size, technologies, signals)

  • Integrated email + LinkedIn finder

  • Pay-as-you-go and tiered plans

Watch out for:

  • Data freshness varies — re-verify before scoring as "Hot"

  • Email accuracy ~60–80% — always validate

  • Bulk export limits apply

Integration: see apollo.md


Clay

Use for: Multi-source enrichment, waterfall lookups, custom scoring logic. When list quality matters more than list size.

Strengths:

  • Waterfall logic: query providers in order and stop at the first verified result (see sourcing-and-enrichment.md for ordering and the bake-off)

  • 100+ data provider integrations

  • AI-powered enrichment (LLM-driven extraction from URLs)

  • Custom columns + scoring formulas

  • Native MCP server

Watch out for:

  • Per-credit pricing can spike on large lists

  • Complexity overhead — easy to over-engineer workflows

Integration: see clay.md


ZoomInfo

Use for: Enterprise B2B + intent data. Mid-market+ buyer profiles.

Strengths:

  • Enterprise-grade firmographic depth

  • Intent signals (companies searching topics relevant to your offer)

  • Best-in-class for >$50K ACV B2B sales

  • Native MCP server

Watch out for:

  • Expensive ($15K+/yr starter)

  • Overkill for SMB prospecting

  • Locked into multi-year contracts typically

Integration: see zoominfo.md


Waterfall aggregators (FullEnrich, LeadMagic)

Use for: Email and phone enrichment through one API call that queries several providers in sequence. The simpler alternative to building a waterfall in Clay.

Watch out for:

  • Coverage and false-positive rates vary by ICP; run the bake-off in sourcing-and-enrichment.md before committing

  • Verify results anyway; finding an address isn't the same as confirming it

Integration: see fullenrich.md and leadmagic.md


Clearbit (legacy)

Clearbit was absorbed into HubSpot (Breeze Intelligence). Its free tools ended in 2025, and new standalone API access is no longer generally available. Use HubSpot's enrichment if you're on HubSpot; otherwise use the providers above.

Integration: see clearbit.md


Hunter / Snov

Use for: Email pattern discovery + lightweight verification on small lists.

Hunter strengths:

  • Domain-based email discovery

  • Built-in deliverability verification

  • Free tier reasonable for occasional use

Snov strengths:

  • Email finder + drip campaigns (overlap with outreach tooling)

  • Bulk verification

  • Cheaper than Hunter at scale

Watch out for:

  • Both are pattern-guessing tools — accuracy depends on the target company's email pattern being inferable

  • Always run results through a dedicated validator (Truelist or similar) before outreach

Integrations: see hunter.md, snov.md


Truelist

Use for: Email deliverability validation before adding contacts to outreach lists. Critical safety step.

Strengths:

  • Single-email sync verification (/api/v1/verify_inline) + bulk async (/api/v1/verify)

  • Returns email_state (ok / email_invalid / risky / unknown / accept_all) + email_sub_state (email_ok / is_disposable / is_role / unknown_error / failed_smtp_check) + did-you-mean typo suggestions

  • Catches catch-all domains, role accounts, spam traps, disposable providers

  • Official MCP server for agent-driven workflows (Claude, Cursor, VS Code)

  • Official SDKs in 7 languages + framework integrations (Django, Laravel, Next.js, Rails, React, Svelte, Vue, WordPress)

  • Native integrations with Mailchimp, Klaviyo, HubSpot, Zapier, Make, n8n, Clay, Salesforce, more

  • Pay-per-email pricing

Why this matters: Cold email reputation craters when bounce rates exceed 2%. Validating before sending is non-negotiable. Apollo/ZoomInfo/Hunter data is often 60–80% accurate — Truelist catches the rest.

Integration: see truelist.md


LinkedIn Sales Navigator

Use for: Manual decision-maker discovery. The gold standard for B2B / SaaS prospecting but only when used as a research tool.

Strengths:

  • Most accurate decision-maker data in the industry

  • Real-time job changes, posts, signals

  • Lead lists, alerts, saved searches

  • Inmail credits (separate channel from cold email)

Hard rules:

  • Never bulk scrape. LinkedIn aggressively bans scrapers. Account ban risk is real and permanent.

  • Use Sales Nav as a research interface — open profiles, read, take notes, capture key data manually.

  • Apollo and other tools claim LinkedIn data via partnerships / public mirroring — verify the source legitimacy before assuming compliance.

Integration: no MCP or API access at consumer level. Manual research only.


BuiltWith / Wappalyzer

Use for: Tech stack qualification (SaaS branch).

BuiltWith:

  • ~50K+ technologies tracked

  • API + bulk lookups (paid)

  • Historical data (when stack changed)

Wappalyzer:

  • Free browser extension; paid API

  • Lighter coverage than BuiltWith

  • Faster for one-off lookups

Cross-reference both for high-confidence tech stack signals.


Crunchbase

Use for: Funding signals (SaaS branch).

Strengths:

  • Free tier shows recent funding events

  • Paid (Pro / Enterprise) unlocks alerts and deep history

  • API access for paid users

Watch out for:

  • Coverage is best for VC-backed companies; bootstrapped + small businesses underrepresented

  • Self-reported data — verify funding amounts independently


GitHub (stargazers / forks / watchers)

Use for: Developer-intent prospecting. Especially powerful for dev-tool SaaS — stargazers of competitor or category-defining repos are in-market signal.

Strengths:

  • Public API, no scraping concerns

  • High signal quality (a starred repo = explicit interest)

  • Forks are an even stronger signal (intent to modify, not just bookmark)

  • Bundled github-prospects.js CLI handles pagination + enrichment + CSV output

  • Free with 5,000 req/hr authenticated rate limit

Watch out for:

  • Only ~5–20% of users publish email — pair with Apollo/Clay/Hunter for enrichment

  • Very-popular repos (100K+ stars) are mostly noise; smaller targeted repos (5K–25K) give better signal density

  • Most prospects are individuals, not company contacts directly — need to figure out their company from company field or LinkedIn

Integration: see github.md


Firecrawl / Browserbase (single-target site research)

Use for: Programmatically extracting content from a prospect's own website that you already found via discovery on platforms like Google Maps, Yelp, or LinkedIn. Not for scraping those platforms themselves.

Firecrawl
  • Best for: "Just give me the page as markdown" — Local SMB website status checks, B2B company about/team page extraction, structured field extraction

  • Strengths: Low overhead, returns clean LLM-ready markdown, handles most JS-rendered sites, has an MCP server

  • API + MCP + SDKs: Node, Python, Go, Rust

Browserbase
  • Best for: When you need real Chromium — JS-heavy pages, cookie consent dialogs, form submission to reach a contact page, session state

  • Strengths: Full browser control via Playwright/Puppeteer; Stagehand provides AI-friendly natural-language extraction; session recordings for debugging

  • API + MCP (Stagehand) + SDKs: Node, Python

Critical compliance line

Both tools can technically point at any URL. The hard rule:

  • ✓ OK: extracting content from a single business's own website (joescoffeeshop.com) that you found through manual discovery

  • ✗ NOT OK: pointing them at google.com/maps, LinkedIn search results, Yelp listings, or any platform whose ToS prohibits bulk extraction

Discovery happens on platforms (manual browser-assisted research). Extraction happens on individual public business sites.

Integrations: see firecrawl.md, browserbase.md


Visitor identification (RB2B, Warmly, Vector)

Use for: Identifying anonymous site visitors as warm intent signals.

Strengths:

  • Pixel-based visitor → company identification

  • High-intent: they came to your site, they're already in research mode

  • Slack / email alerts on key visits

Watch out for:

  • Privacy/GDPR considerations — verify your privacy policy disclosures

  • Person-level identification raises higher concerns than company-level

Integration: see rb2b.md

Built into a site platform (Ploy ◆)

Some site platforms identify visitors natively. Ploy, a Verified Partner of this repository (disclosure, not endorsement), returns person, company, title, and pages viewed for visitors to sites hosted on it, with contact enrichment alongside.

Watch out for:

  • Only works if the site is hosted on Ploy; for any other site use a pixel tool like RB2B, Warmly, or Vector

  • Metered by plan (as of 2026-10: 50 enrichments a month on Starter, 1,000 on Pro)

  • Ploy says no consent banner is needed; the same privacy and person-level cautions as above still apply, and the legal call is yours

Integration: see ploy.md


Free / browser-only fallbacks

When the user has no paid tools, lean on:

  • Google Search — exact business name + city + role searches

  • LinkedIn (manual, no scraping) — company pages, employee lookups

  • Crunchbase free tier — funding events

  • Wappalyzer browser extension — tech stack at a glance

  • Hunter.io free tier — 25 lookups/month

  • Google Maps — for Local SMB discovery

  • Business websites + About pages — primary source for any claim

  • News sites + press releases — trigger event monitoring via Google Alerts

Slower than tooled-up workflows, but produces high-quality smaller lists if the user is willing to do the work.


Sequencing recommendations

A typical full-stack prospecting workflow:

  1. Define ICP from product-marketing context (no tools needed)

  2. Initial list from Apollo or ZoomInfo (firmographic filter)

  3. Enrich with Clay (waterfall: tech stack, funding, trigger events)

  4. Decision-maker mapping in LinkedIn Sales Nav (manual)

  5. Email pattern discovery with Hunter or Apollo's built-in

  6. Email validation with Truelist before final list

  7. Hand off to cold-email skill for outreach copy

Adapt this sequence based on which tools the user actually has.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Corey Haines
Publisher
Corey Haines (Community)
Source
coreyhaines31/marketingskills · skills/prospecting · commit 96798cf
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Corey Haines or Corey Haines.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download prospecting.zip