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/enrichment-playbook.md

Waterfall Enrichment and Cache Reuse

Load this when a prospect list needs multiple data providers, repeated lookups, or a credit budget. Keep the prospecting skill's ICP, source lineage, contact verification, and compliance rules. This is a workflow design, not a new API or a promise of coverage.

Define the Success Condition Before Calling Providers

For each missing field, specify the required input, acceptable output, freshness, and maximum cost. A nonempty response is insufficient: a guessed address, a wrong-company match, or an old job title may fail the acceptance rule.

Example: find a published business contact for an ICP-fit account, then verify deliverability separately. A provider returning a name alone has not completed that task. Do not expand to personal emails simply because work-email providers found nothing.

Order providers by fit for this field, observed coverage, cost, and latency. There is no universal Hunter/Apollo/FullEnrich order. Use the user's existing connected tools; a manual public-source lookup is also a valid step.

Run a Waterfall, Not Every Provider

  1. Normalize the inputs and check existing verified CRM fields.

  2. Read the exact cache entry for the first provider lookup.

  3. If no reusable entry exists, perform that lookup within the authorized budget.

  4. Validate the returned identity and field; record source and retrieval time.

  5. Stop when the acceptance rule is satisfied. Otherwise advance to the next suitable provider.

  6. If all steps return no acceptable result, retain the row as unresolved with a reason. Do not fill blanks with invented values.

Lookup outcomeNext action
Fresh, accepted resultReuse it; stop this field's waterfall
Genuine no-matchAdvance; optionally cache the no-match briefly
Wrong entity or invalid outputRecord rejection; advance if another source can resolve it
Authentication/permission errorRepair the connection; do not label the contact nonexistent
Rate limit, timeout, provider outageRespect provider retry guidance and budget; defer or use an authorized independent source
Missing required inputResolve identity first; another identical empty-input call will not help

Apply conditions per row. An already verified contact should not spend credits discovering the same field again. Dependent steps wait for the preceding result; independent missing fields may run concurrently within provider limits.

For Clay, configure the provider sequence, inputs, and run conditions using its waterfall documentation. Its workflow guidance distinguishes publishing a setup from running it and spending credits. Other tools need their own documented execution semantics.

Exact Cache Keys

Use a structured key with these dimensions:

workspace/account + provider + endpoint/version + normalized inputs + requested fields/options

Keep account scope separate even when two customers query the same domain. Normalize domains consistently (case, URL host, trailing dot); remove URL paths only for domain-based lookups. Preserve distinctions a provider treats as meaningful: person versus company, subdomain, country, filters, and email local-part rules. A company-name fuzzy match is not an exact cache hit.

Store status, accepted fields, entity identifiers, source, fetched time, expiry, and validation outcome. Never store API keys in keys or result logs. Restrict access to contact data and honor deletion/retention requirements.

  • Fresh accepted hit: reuse without another charged call.

  • Expired hit: refresh fields that require current evidence; label any provisional stale data explicitly.

  • Miss: fetch the provider; a cache endpoint's documented 404 may mean only that the cache has no entry, not that the provider found no company.

  • Negative hit: apply a separate, usually shorter expiry; changing inputs invalidates the match.

  • Error: keep operational failures distinct from no-match records.

Merge accepted fields with provenance instead of overwriting verified CRM data with nulls or weaker matches. For concurrent duplicate lookups, reuse one in-flight request where supported; guard the final write so a late weaker result cannot replace a newer verified one.

Deliverable and Pilot

Return a table with row identity, missing field, provider order, acceptance rule, cache decision, source/date, result, verification status, cost, and unresolved reason. Track cost per accepted field and verified contact, cache reuse, no-match rate, invalid-match rate, and sampled accuracy. Report actual measured savings; a cache does not guarantee a particular reduction.

Pilot on representative rows before a broad run: fresh hit, expired hit, true no-match, ambiguous company, provider failure, and duplicate input. Compare with a single-provider control under the same acceptance rule and budget. Pass qualified rows to cold-email only after contact verification; use the revops inbound-routing playbook for live form submissions.

Patterns adapted from eliasstravik's MIT-licensed GTM engineering toolkit. This playbook works with existing providers or manual research.

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