Prospecting
Corey HainesCommunityCreated by Corey Haines
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AutoGineer summary
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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
Download the skill as a ZIP:
https://autogineer.com/agent-skills/coreyhaines31/prospecting/downloadUnzip 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:
| Branch | Sell to | What "qualified" looks like | Primary sources |
|---|---|---|---|
| SaaS | Other SaaS companies / digital businesses | ICP fit + tech stack match + growth signals (funding, hiring, product velocity) | LinkedIn, BuiltWith, Crunchbase, Apollo, Clay, ProductHunt |
| B2B | Non-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 SMB | Local small businesses (shops, gyms, restaurants, clinics, salons, services) | Active business + website status + proximity + decision-maker access | Google Maps, Yelp, local directories, Facebook, business websites |
| Demand-signal | Early-stage: your first customers, design partners, or beta users | Evidence of the exact pain/demand/timing signal — a cited public source, not just firmographic fit | Forums, 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:
SaaS → see references/saas-prospecting.md
B2B → see references/b2b-prospecting.md
Local SMB → see references/local-prospecting.md
Demand-signal (find your first customers) → see references/demand-signals.md
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:
Firmographic fit — industry, company size, revenue band, geography, business model
Technographic fit (SaaS branch) — what tools they already use, what they're missing
Buying signal — why now? (trigger event, funding, hiring, new initiative, dissatisfaction with current vendor, recent move/expansion)
Decision-maker profile — role, seniority, what they care about
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.
| Score | Definition |
|---|---|
| Hot | Strong ICP fit + clear buying signal + decision-maker accessible + verified contact |
| Warm | ICP fit + softer or older signal + contact verifiable |
| Cold | Loose ICP fit OR no clear signal OR contact unverified |
| Skip | Disqualifier 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.
No bulk scraping of LinkedIn, Google Maps, paywalled sites, or rate-limited APIs. Browser is an assisted research tool, not a scraper.
No CAPTCHA, login wall, or bot protection bypass. If a site requires it, work with what's publicly visible.
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.).
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.
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.
Rate limit yourself. Even on public sources, space requests. Don't fingerprint as a bot.
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.
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.mdif presentTarget 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 |
|---|---|
| Apollo | B2B / SaaS firmographic + contact discovery |
| Clay | Multi-source enrichment, waterfall lookups, custom scoring |
| FullEnrich or LeadMagic | Waterfall email and phone enrichment through one API |
| TheirStack | Hiring signals and tech stacks from job posts |
| ZoomInfo | Enterprise B2B contact + intent data |
| Hunter or Snov | Email pattern guessing and verification |
| Truelist | Email deliverability validation (before adding to outreach list) |
| LinkedIn Sales Navigator | Decision-maker mapping (manual, no scraping) |
| BuiltWith / Wappalyzer | Tech stack qualification (SaaS branch) |
| Crunchbase | Funding signals (SaaS branch) |
| GitHub | Stargazers / forks of competitor or adjacent repos (dev-tool SaaS branch) |
| Google Maps + browser | Local SMB discovery |
| Firecrawl / Browserbase | Programmatic 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,notesLocal SMB columns:
score,business,category,area,distance_km,website_status,website_url,social_urls,phone,email,source_urls,why_prospect,confidence,verified_date,notesAlways 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
Starting discovery without an ICP. Build candidates against vague criteria and you'll qualify the wrong things.
Treating data sources as authoritative without cross-checks. Apollo and ZoomInfo are out of date often; verify before scoring as "Hot."
Adding contacts without email verification. Cold email reputation tanks fast with bounces — always validate.
Bulk scraping LinkedIn or Google Maps. Real risk: account suspension + ToS violation. Browser as an assisted tool only.
Mixing branches. Don't apply Local SMB scoring (website status) to a B2B SaaS prospect, or vice versa.
"Hot" labels without buying signals. ICP fit alone is not enough — the signal is what makes the timing right.
No source URLs. Every claim should be traceable to a public source. Future outreach depends on this lineage.
Ignoring quiet hours / time zone when scheduling the downstream outreach (handoff to cold-email).
Forgetting to retain consent / lineage records. Required for GDPR DSARs and CAN-SPAM audits.
Task-Specific Questions
Which branch — SaaS, B2B, Local SMB, or Demand-signal (early-stage, finding your first customers)?
What's your ICP? (Or: should I pull from your product-marketing context?)
How many qualified leads do you want?
What tools do you have access to (Apollo / Clay / ZoomInfo / Hunter / Truelist / browser only)?
What's the triggering buying signal you care most about?
Geography or radius (Local SMB / B2B)?
Chat table or CSV?
Tool Integrations
For implementation, see the tools registry. Key prospecting tools:
| Tool | Best For | MCP | Guide |
|---|---|---|---|
| Apollo | B2B / SaaS firmographic + contact discovery | ✓ | apollo.md |
| Clay | Multi-source enrichment + waterfall | ✓ | clay.md |
| FullEnrich | Waterfall email + phone enrichment | ✓ | fullenrich.md |
| LeadMagic | Email, phone, and job-change enrichment | ✓ | leadmagic.md |
| TheirStack | Hiring signals and tech stacks from job posts | ✓ | theirstack.md |
| Apify | Structured data from public directories (never LinkedIn) | ✓ | apify.md |
| ZoomInfo | Enterprise B2B contact + intent | ✓ | zoominfo.md |
| Hunter | Email pattern + verification | ✓ | hunter.md |
| Snov | Email finder + verifier | - | snov.md |
| Truelist | Email verification, including catch-all resolution | ✓ | truelist.md |
| Outreach | Sales engagement (post-list) | ✓ | outreach.md |
| RB2B | Visitor identification (warm intent) | - | rb2b.md |
| Ploy ◆ | Visitor identification on Ploy-hosted sites (one option alongside RB2B and other visitor-ID tools) | - | ploy.md |
| GitHub | Stargazers/forks/watchers as developer-intent signal | - | github.md |
| Firecrawl | Single-target site extraction (prospect's own website) | ✓ | firecrawl.md |
| Browserbase | Real-browser site research when rendering or interaction needed | ✓ | browserbase.md |
Related Skills
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
- ATTRIBUTION.mdAdded by AutoGineer883 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md19.9 KiB
- evals/evals.json17.9 KiB
- references/account-research.md3.7 KiB
- references/b2b-prospecting.md4.9 KiB
- references/compliance.md10.8 KiB
- references/data-sources.md13.1 KiB
- references/demand-signals.md9.9 KiB
- references/enrichment-playbook.md5.2 KiB
- references/local-prospecting.md8.0 KiB
- references/saas-prospecting.md5.9 KiB
- references/signal-plays.md13.6 KiB
- references/sourcing-and-enrichment.md6.6 KiB
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:
| Rank | Signal | Why it works | Typical source |
|---|---|---|---|
| 1 | Your own product usage: a signup from a company domain, a plan limit hit, a big upload, a team invite | They already chose you once | Your product analytics, billing |
| 2 | Past champions changing jobs | Former users bring the tool with them; vendors report win rates roughly double when the buyer has used the product before | CRM contacts + job-change tracking (UserGems, Clay, manual LinkedIn checks) |
| 3 | High-intent website visits: pricing, comparison, integration pages | Active evaluation | Visitor identification (RB2B, Warmly, Vector), your analytics |
| 4 | Engagement with you or a competitor: comments on your posts or a competitor's, community questions | Public interest in the problem | Trigify, Common Room, social listening |
| 5 | Hiring in the function you serve, or a new leader in it | New budget and a mandate to change things | Job boards (TheirStack, PredictLeads), LinkedIn |
| 6 | Funding, launches, expansion | Budget, plus pressure to grow fast | Crunchbase, news, press releases |
| 7 | Tech stack changes: adding or dropping a tool next to yours | A related decision is in motion | BuiltWith, Wappalyzer, job-post tech mentions |
| 8 | Generic third-party intent | Weakest, and noisy | Bombora-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.
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.
Enrich and rank every contact: company, role, industry, headcount. Score them against your ICP like any other list.
Match against target accounts to find first- and second-degree paths into the companies you want.
Start with your calendar. Recent meetings show who is in a buying moment right now.
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.
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:
| Signal | Act within | After that |
|---|---|---|
| Product usage spike, limit hit | Same day (ideally within minutes) | Treat as a normal product-qualified lead |
| Pricing or comparison page visit | 24 hours | Drop to the general list |
| Champion job change | 30–90 days in the new role | They've already chosen their stack |
| New leader in the function | First 90 days | Priorities are set |
| Job post for the function | While the post is open, up to ~60 days | Hire made, budget allocated |
| Funding announcement | 30–60 days | Old news; don't congratulate on it |
| Tech install or removal | 30 days | Decision 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:
| Signal | Play | Opening angle | Channel order |
|---|---|---|---|
| Product limit hit | Sales-assist | Offer to help them get more from the plan they're outgrowing | Email from a founder or account owner within minutes, then LinkedIn |
| Champion job change | Reunion | Reference the work they did with you before; ask how the new team handles it | LinkedIn first (they're updating their profile), then email |
| Pricing page visit (identified) | Evaluation help | Don't mention the visit. Lead with the decision they're probably weighing | Email, then call for Tier 1 |
| New leader in the function | First 90 days | The thing new leaders in that role usually fix first, with proof | LinkedIn connect, then email |
| Hiring for the function | Bridge the gap | What they can get done before the hire lands, or what the hire will need | |
| Competitor engager | Alternative | The problem they engaged with, not the competitor | LinkedIn, 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.
| Signal | Gap to verify | How to check it from outside | Fits an offer like |
|---|---|---|---|
| Recent funding or a new marketing leader | The site hasn't changed in a long time, or doesn't match the new story | Wayback Machine snapshots, the copyright year, positioning that doesn't match the funding announcement | Website, CRO, positioning |
| Hiring several SDRs or BDRs | The outbound stack doesn't match the plan | The tools named in the job post, sending-domain DNS (SPF, DKIM, DMARC), the tech stack | Email infrastructure, enrichment, deliverability |
| Hiring for repetitive work (data entry, reporting, lead research, CRM admin) | The job post describes tasks that can be automated | The responsibilities list in the post itself | Automation, RevOps, AI agents |
| Running paid ads | No visible ad or analytics tags | Page source, browser network tab, or a tag-checker extension (Meta Pixel Helper, Google Tag Assistant) | Tracking and attribution setup |
| Running paid ads | Paid traffic lands on the homepage | The destination link on each ad in the Meta Ad Library or LinkedIn Ad Library | Landing pages, CRO |
| Running the same ads for months | Creative fatigue | Start dates in the Meta Ad Library; the Google Ads Transparency Center for search and YouTube | Ad creative |
| Many locations | Missing or thin location pages | Store locator count vs. pages found with site:domain.com/locations; Google Business Profiles per location | Local SEO |
| Many integrations or use cases | Few pages about them | The integrations directory vs. a site: search for integration or use-case pages | Programmatic SEO, content |
| A lead magnet (ebook, calculator, webinar) | No follow-up after opt-in | Opt in with an address you control and log every email for 14 days, then unsubscribe | Email nurture, lifecycle |
| Expanding into a new country | The site isn't localized for it | Language switcher, hreflang tags, local currency and payment methods on pricing | Localization, international SEO |
Rules for gap plays:
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.
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.
Re-check before sending. Gaps get fixed. Re-verify within 7 days of the first touch, or drop the gap from the message.
The gap must map to your offer. Spotting a problem you can't fix is research, not a play.
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.
| Tier | Accounts | Research | Channels | Copy |
|---|---|---|---|---|
| Tier 1 (1:1) | Top ~25–50 by fit and signal | A full account brief (see account-research.md), mobile numbers | Email, LinkedIn, phone, video, possibly direct mail | Written per person; a human reviews every message |
| Tier 2 (1:few) | Segments of 20–200 sharing one specific pain | Segment research plus one personal line | Email + LinkedIn | Written per segment, with a personal opener; a human reviews a sample |
| Tier 3 (1:many) | Everyone else who fits | The segment definition is the research | Written 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 type | Options | Agent access |
|---|---|---|
| Job postings and hiring | TheirStack, PredictLeads, LinkedIn Jobs (manual) | TheirStack has an MCP; PredictLeads has an API |
| Job changes | UserGems, Clay job-change tracking, manual checks of past champions | Clay MCP |
| Website visitors | RB2B (US, person-level), Warmly, Vector, Koala | Mostly webhooks into your CRM or a Zap |
| Social and community engagement | Trigify, Common Room | Both have APIs and MCPs |
| Funding and news | Crunchbase, news search, Exa | Exa MCP; Crunchbase API on paid plans |
| Public posts and announcements | X search (Grok searches X directly), LinkedIn posts (manual), news search | Grok via the xAI API; Exa MCP |
| Ad activity | Meta Ad Library, Google Ads Transparency Center, LinkedIn Ad Library | Meta Ad Library API (political and EU ads only; check its current scope); otherwise browser research |
| Tech stack | BuiltWith, Wappalyzer, tech mentions in job posts | APIs |
| Product usage | Your own analytics and billing events | Webhooks 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
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