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Prospecting

Corey HainesCommunityCreated by Corey Haines

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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/signal-plays.md

Signal Plays

A list tells you who could buy. A signal tells you who might buy now. This reference turns signals into outbound plays: which signals to trust, how fresh they need to be, what to do when one fires, and how much effort each account deserves.

Signals are a timing and relevance filter. They don't replace ICP fit. A strong signal at a company outside your ICP is still a skip, and a great-fit account with no signal can still get a well-aimed message built on its situation.

Rank signals by how close they are to you

The closer the signal is to your product and your past customers, the better it converts. Work down this list and stop where you have enough volume:

RankSignalWhy it worksTypical source
1Your own product usage: a signup from a company domain, a plan limit hit, a big upload, a team inviteThey already chose you onceYour product analytics, billing
2Past champions changing jobsFormer users bring the tool with them; vendors report win rates roughly double when the buyer has used the product beforeCRM contacts + job-change tracking (UserGems, Clay, manual LinkedIn checks)
3High-intent website visits: pricing, comparison, integration pagesActive evaluationVisitor identification (RB2B, Warmly, Vector), your analytics
4Engagement with you or a competitor: comments on your posts or a competitor's, community questionsPublic interest in the problemTrigify, Common Room, social listening
5Hiring in the function you serve, or a new leader in itNew budget and a mandate to change thingsJob boards (TheirStack, PredictLeads), LinkedIn
6Funding, launches, expansionBudget, plus pressure to grow fastCrunchbase, news, press releases
7Tech stack changes: adding or dropping a tool next to yoursA related decision is in motionBuiltWith, Wappalyzer, job-post tech mentions
8Generic third-party intentWeakest, and noisyBombora-style intent feeds, review-site intent

Stack signals before acting on the weaker ones. Hiring a lifecycle marketer plus an ESP in the stack plus a fit score above your threshold is worth a sequence. Any one of those alone usually isn't.

Warm paths: your network is a signal too

Before buying a list, mine the relationships you already have. A warm introduction gets read when the twentieth cold email of the day doesn't, and AI-written outreach makes that gap wider.

  1. Export your network. LinkedIn connections (Settings → Data privacy → Get a copy of your data), calendar attendees, and inbox contacts. LinkedIn's export includes emails only for connections who allow it.

  2. Enrich and rank every contact: company, role, industry, headcount. Score them against your ICP like any other list.

  3. Match against target accounts to find first- and second-degree paths into the companies you want.

  4. Start with your calendar. Recent meetings show who is in a buying moment right now.

  5. Find one connector per vertical: someone trusted by buyers who ignore cold outreach (an agency owner who knows every other agency owner). Pay them the way you'd pay for a qualified meeting, and disclose the arrangement.

  6. Double opt-in intros only. Ask the connector, then the target, before anyone is introduced. Keep a human approving every intro, and never ask one contact to take intros for two vendors in the same week. Trust is the asset; spend it slowly.

Adapted from Cody Schneider's podcast with Chris of Super Connector (October 2026).

Freshness windows

A signal decays. Act inside these windows or downgrade it:

SignalAct withinAfter that
Product usage spike, limit hitSame day (ideally within minutes)Treat as a normal product-qualified lead
Pricing or comparison page visit24 hoursDrop to the general list
Champion job change30–90 days in the new roleThey've already chosen their stack
New leader in the functionFirst 90 daysPriorities are set
Job post for the functionWhile the post is open, up to ~60 daysHire made, budget allocated
Funding announcement30–60 daysOld news; don't congratulate on it
Tech install or removal30 daysDecision done

Record the signal date on every lead. A lead sheet without signal dates can't be prioritized.

From signal to play

Every signal you track should map to a specific play, so nobody improvises the angle at send time:

SignalPlayOpening angleChannel order
Product limit hitSales-assistOffer to help them get more from the plan they're outgrowingEmail from a founder or account owner within minutes, then LinkedIn
Champion job changeReunionReference the work they did with you before; ask how the new team handles itLinkedIn first (they're updating their profile), then email
Pricing page visit (identified)Evaluation helpDon't mention the visit. Lead with the decision they're probably weighingEmail, then call for Tier 1
New leader in the functionFirst 90 daysThe thing new leaders in that role usually fix first, with proofLinkedIn connect, then email
Hiring for the functionBridge the gapWhat they can get done before the hire lands, or what the hire will needEmail
Competitor engagerAlternativeThe problem they engaged with, not the competitorLinkedIn, then email

Write the angle as the problem the signal implies. "Saw you raised a Series A" is a fact everyone else sent. "Most teams that just raised are told to double pipeline in two quarters, and the site usually becomes the bottleneck" is a reason to reply.

Gap plays: a signal plus a gap you can see

The strongest services and tooling plays pair two things: a signal that the company is spending or growing, and a gap you can verify from outside that your offer fixes. The signal says they have budget and a reason to act. The gap gives you a specific, checkable opener instead of a guess.

SignalGap to verifyHow to check it from outsideFits an offer like
Recent funding or a new marketing leaderThe site hasn't changed in a long time, or doesn't match the new storyWayback Machine snapshots, the copyright year, positioning that doesn't match the funding announcementWebsite, CRO, positioning
Hiring several SDRs or BDRsThe outbound stack doesn't match the planThe tools named in the job post, sending-domain DNS (SPF, DKIM, DMARC), the tech stackEmail infrastructure, enrichment, deliverability
Hiring for repetitive work (data entry, reporting, lead research, CRM admin)The job post describes tasks that can be automatedThe responsibilities list in the post itselfAutomation, RevOps, AI agents
Running paid adsNo visible ad or analytics tagsPage source, browser network tab, or a tag-checker extension (Meta Pixel Helper, Google Tag Assistant)Tracking and attribution setup
Running paid adsPaid traffic lands on the homepageThe destination link on each ad in the Meta Ad Library or LinkedIn Ad LibraryLanding pages, CRO
Running the same ads for monthsCreative fatigueStart dates in the Meta Ad Library; the Google Ads Transparency Center for search and YouTubeAd creative
Many locationsMissing or thin location pagesStore locator count vs. pages found with site:domain.com/locations; Google Business Profiles per locationLocal SEO
Many integrations or use casesFew pages about themThe integrations directory vs. a site: search for integration or use-case pagesProgrammatic SEO, content
A lead magnet (ebook, calculator, webinar)No follow-up after opt-inOpt in with an address you control and log every email for 14 days, then unsubscribeEmail nurture, lifecycle
Expanding into a new countryThe site isn't localized for itLanguage switcher, hreflang tags, local currency and payment methods on pricingLocalization, international SEO

Rules for gap plays:

  1. Verify the gap; never assume it. Record what you checked, the date, and a screenshot or URL. An agent asked to find gaps will invent them unless every gap needs evidence. "No gap found" is a valid result, the same as "no hook found" in account-research.md.

  2. Know what can't be seen from outside. Server-side tracking (Meta's Conversions API, server-side Google Tag Manager) doesn't show in page source, so a missing browser tag isn't proof of missing tracking. Ask, don't accuse. A homepage is also a normal destination for brand-name search ads, and an ad running for months may be the winner rather than tired. Ad longevity is a proxy, not proof.

  3. Re-check before sending. Gaps get fixed. Re-verify within 7 days of the first touch, or drop the gap from the message.

  4. The gap must map to your offer. Spotting a problem you can't fix is research, not a play.

  5. Lead with the observation and a question, not a verdict. "Your Meta ads for the spring launch point to the homepage. Is that on purpose?" gets replies. "Your landing pages are wasting your ad spend" gets deleted. Offer the evidence, and the teardown, only after they say yes (see the cold-email skill's outbound plays reference).

Searching for these by hand is slow, which is why the plays used to be rare. Agents with web, ad-library, and X search access (Grok, for example, searches X directly) can build the list. A human still reviews the evidence for Tier 1 and a sample for Tier 2. Once a play gets replies, run it on a schedule with the signal-sweep loop in the marketing-loops skill.

Two worked examples

A services agency selling to B2B SaaS (for example, a CRO and landing page agency)

  • Signals: funding in the last 60 days; a new VP Marketing or head of growth; open roles for growth or performance marketers; a redesigned site or new pricing page; paid search or paid social campaigns launching.

  • Play: value first, built on a verified gap from the gap plays table. Offer a short teardown of their actual page. Send it only after they say yes. See the cold-email skill's outbound plays reference.

  • Volume: about 50 well-researched accounts a week beats 5,000 generic sends. Agencies rely on depth.

A self-serve SaaS tool (for example, an email verification product)

  • Signals: signups from company domains; credit or plan limits hit; large list uploads; team invites. Off-product signals include companies hiring lifecycle, RevOps, or SDR roles and cold-email tools appearing in their stack.

  • Play: product-led outbound for usage signals, problem-led cold outbound for the rest. The outbound plays reference covers both.

  • Volume: usage signals are few but hot. Cold lists can be larger, but every send has to model the deliverability the product sells.

Account tiers

Tiers decide how much research and how many channels each account gets. Assign the tier before writing anything.

TierAccountsResearchChannelsCopy
Tier 1 (1:1)Top ~25–50 by fit and signalA full account brief (see account-research.md), mobile numbersEmail, LinkedIn, phone, video, possibly direct mailWritten per person; a human reviews every message
Tier 2 (1:few)Segments of 20–200 sharing one specific painSegment research plus one personal lineEmail + LinkedInWritten per segment, with a personal opener; a human reviews a sample
Tier 3 (1:many)Everyone else who fitsThe segment definition is the researchEmailWritten per segment; relevance comes from how tightly the segment is defined

Keep campaigns small. Several vendor and agency datasets show reply rates falling as campaign size grows, with campaigns of 50 or fewer recipients replying at roughly twice the rate of campaigns over 1,000.

Tools for detecting signals

Signal typeOptionsAgent access
Job postings and hiringTheirStack, PredictLeads, LinkedIn Jobs (manual)TheirStack has an MCP; PredictLeads has an API
Job changesUserGems, Clay job-change tracking, manual checks of past championsClay MCP
Website visitorsRB2B (US, person-level), Warmly, Vector, KoalaMostly webhooks into your CRM or a Zap
Social and community engagementTrigify, Common RoomBoth have APIs and MCPs
Funding and newsCrunchbase, news search, ExaExa MCP; Crunchbase API on paid plans
Public posts and announcementsX search (Grok searches X directly), LinkedIn posts (manual), news searchGrok via the xAI API; Exa MCP
Ad activityMeta Ad Library, Google Ads Transparency Center, LinkedIn Ad LibraryMeta Ad Library API (political and EU ads only; check its current scope); otherwise browser research
Tech stackBuiltWith, Wappalyzer, tech mentions in job postsAPIs
Product usageYour own analytics and billing eventsWebhooks into your CRM

See the tools registry for setup. A scheduled sweep of these sources is the signal-sweep loop in the marketing-loops skill.

Common mistakes

  • Treating any funding round as a buying signal for everything.

  • Opening with the signal itself ("Congrats on the raise"). Use it to choose the angle, then talk about their problem.

  • Acting on stale signals. A six-month-old job change is just a job.

  • Mentioning website visits that the prospect doesn't know were tracked. It reads as surveillance.

  • Running every account at the same depth. Tier first.

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

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Download ZIP

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