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prospecting

为企业服务、SaaS、当地商家或早期产品寻找并筛选潜在客户,依据来源核实匹配度和购买信号,验证邮箱,并整理优先级名单或需求证据报告。

原文查看原文说明

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," "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.

集成工具LinkedIn

实测评分 未实测

查看安装方法

适用场景

  • 整理企业销售候选名单
  • 寻找目标地区的商家
  • 从公开需求中发现首批客户
  • 联系前调查重点企业

中文介绍

功能

此技能可帮助您寻找潜在客户,核对他们与目标条件的匹配程度,并安排联系优先级。它可以明确理想客户画像(ICP),调查行业、企业规模和地区,查找招聘或融资等购买信号,并确认决策者的联系途径。调查结果可整理为表格或 CSV,附上来源、可信度和核实日期。寻找首批客户时,还会汇总具体问题或需求的证据。

适用场景

当您需要筛选企业服务或 SaaS 销售对象、调查特定地区的商家、寻找早期客户或试用合作方,或在联系重点企业前准备有来源依据的调查摘要时,可以使用此技能。

使用示例

  • “找出 25 家符合这些条件的企业,并按购买信号排序。”
  • “调查这个地区的商家,整理其网站情况和公开联系方式。”
  • “根据公开分享的问题,寻找可能的首批客户。”

注意事项

如果账户可使用 Apollo 或 Clay,技能会按可用权限使用;否则会通过浏览器调查公开信息。它会核实邮箱是否可能送达。此技能禁止批量收集 LinkedIn 或 Google Maps 数据,也禁止绕过身份验证。使用数据和联系潜在客户时,需遵守适用条款与法律。撰写和发送销售联系内容属于 cold-email 的范围。

本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。

文档检查

AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。

安全性发送数据、删除文件、执行命令等是否有说明
B部分不足资料要求验证邮箱并禁止抓取 LinkedIn,但公开信息收集方式较多。
安装难易度所需工具和 API 密钥是否少且有说明
B部分不足资料提到 Apollo、Clay 和浏览器调查,但未固定所需权限或工具。

不计入评分。 由 AI(OpenAI Codex)于 2026年10月24日 评估。仅供参考,安装前请同时查看原文。

如果您认为评估有误,请申请复核

请写明哪一项有误以及原因。无需登录。我们会对照 SKILL.md 重新评估,并在此处更新结果。

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

包含的文件(12)

  • SKILL.md19.7 KB
  • evals/evals.json15.2 KB
  • references/account-research.md3.7 KB
  • references/b2b-prospecting.md4.9 KB
  • references/compliance.md10.8 KB
  • references/data-sources.md13.1 KB
  • references/demand-signals.md9.9 KB
  • references/enrichment-playbook.md5.2 KB
  • references/local-prospecting.md8.0 KB
  • references/saas-prospecting.md5.9 KB
  • references/signal-plays.md8.0 KB
  • references/sourcing-and-enrichment.md6.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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), 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

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

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