Files
marketingskills/skills/ads/SKILL.md
T
Corey Haines f86637eace feat: add prospecting skill + truelist integration (#308)
* feat: add prospecting skill + truelist integration

New skill: skills/prospecting/
- SKILL.md (251 lines, well under 500 limit): branch picker for SaaS / B2B /
  Local SMB, shared 5-phase framework (ICP -> discovery -> qualify -> score ->
  output), compliance guardrails, tool selection quick-picks, output formats
- references/saas-prospecting.md: tech stack signals, funding/hiring triggers,
  SaaS-specific sources and qualification
- references/b2b-prospecting.md: industry/firmographic signals, trigger events,
  decision-maker mapping, B2B-specific sources
- references/local-prospecting.md: 4-tier website status classification,
  browser-assisted research workflow (generalized from the local-client-
  prospector pattern), proximity scoring
- references/data-sources.md: deep dives on Apollo, Clay, ZoomInfo, Clearbit,
  Hunter, Snov, Truelist, LinkedIn Sales Nav, BuiltWith, Crunchbase, RB2B,
  with sequencing recommendations across the three branches
- references/compliance.md: CAN-SPAM, GDPR, CASL, platform ToS (LinkedIn,
  Google Maps, Apollo/ZI/Clearbit), anti-patterns, audit checklist
- evals/evals.json: 6 evals (2 SaaS, 2 B2B, 1 Local SMB, 1 deliverability)

New integration:
- tools/integrations/truelist.md: email deliverability validation
  (Deliverable / Risky / Undeliverable / Unknown classification)

Registry + marketplace wiring:
- tools/REGISTRY.md: truelist row + new Email Verification category section
- .claude-plugin/marketplace.json: bumped to 2.1.0, prospecting added to
  plugin description
- VERSIONS.md: prospecting 1.0.0 + 2.1.0 changelog entry
- README.md: skill table re-synced, prospecting added to ASCII flow under
  Sales & GTM column

All 41 skills pass validation. sync-skills.js is idempotent.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* feat(prospecting): add GitHub stargazers/forks/watchers as discovery channel

Net-new in this commit:
- tools/clis/github-prospects.js: zero-dep Node CLI with commands
  stargazers / forks / watchers / user / rate-limit. Pagination via Link header,
  optional --enrich for full profile data, --with-email / --with-company /
  --with-blog filters, --format csv|json output, --dry-run preview. Uses
  GITHUB_TOKEN for 5000/hr rate limit (vs 60/hr unauthenticated).
- tools/integrations/github.md: integration guide covering auth, rate limits,
  endpoints, workflows for SaaS prospecting, compliance notes (public API, not
  scraping), CLI reference.

Skill updates:
- skills/prospecting/SKILL.md: added GitHub to the tool selection quick picks
  and to the tool integrations table.
- skills/prospecting/references/saas-prospecting.md: added GitHub to Tier 3
  buying signals plus a dedicated "GitHub prospecting pattern (when audience
  is developers)" subsection with end-to-end workflow.
- skills/prospecting/references/data-sources.md: added GitHub deep-dive
  section between RB2B and Free fallbacks.

Registry:
- tools/REGISTRY.md: github row in Tool Index, new Developer Intent / GitHub
  category section.

All 41 skills still pass validation. sync-skills.js still no-op.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* refactor(prospecting): apply review suggestions

CLI hardening + optimization:
- github-prospects.js: encodeURIComponent on username path interpolation
  (defense in depth; GitHub usernames are restricted enough that this is safe
  in practice, but good hygiene).
- github-prospects.js: refactored enrichUsers to filter inline and support
  --target N early termination. Previously, --with-email on a 1000-star repo
  would enrich all 1000 users before filtering down to the ~50 that match.
  Now you can pass --target 25 to stop as soon as 25 matches are found,
  saving API quota on restrictive filters.
- github.md: documented the new --target flag.

Reverse cross-references (so prospecting is discoverable from sibling skills):
- cold-email: added prospecting as the natural upstream skill
- customer-research: added "Translating customer research into an ICP for
  outbound" hand-off to prospecting
- competitor-profiling: distinguished from prospecting ("this skill does deep
  research on specific accounts; prospecting builds the initial list")

All 41 skills still pass validation. sync-skills.js still no-op.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* fix(truelist): align integration doc with actual OpenAPI spec

Source of truth: Truelist-Labs/truelist-openapi (OpenAPI 3.1).

The earlier integration doc had inferred (and wrong) endpoint paths, request
shapes, and status enum values. Corrected against the published spec:

Base URL: https://api.truelist.io
Endpoints (real):
- POST /api/v1/verify_inline?email=... (sync single, email is query param)
- POST /api/v1/verify (async bulk, body: {emails: [...]})
- GET /me (account info)

Real email_state enum:
- ok, email_invalid, risky, unknown, accept_all
(not the inferred "Deliverable / Risky / Undeliverable / Unknown")

Real email_sub_state enum:
- email_ok, is_disposable, is_role, unknown_error, failed_smtp_check

Also corrected:
- Truelist has an official MCP server (Truelist-Labs/truelist-mcp) — was
  marked as MCP unavailable
- Truelist has 7 official SDKs (Node, Python, Ruby, PHP, Go, Java, .NET) +
  framework integrations (Django, Laravel, Next.js, Rails, React, Svelte,
  Vue, WordPress) — was marked as SDK unavailable
- Native integrations with Mailchimp, Klaviyo, HubSpot, Zapier, Make, n8n,
  Clay, Salesforce, ActiveCampaign, Brevo, ConvertKit, Drip, BigCommerce,
  Go High Level — was unlisted
- Rate limits: 10 req/s per endpoint (was unspecified)

Files updated:
- tools/integrations/truelist.md: full rewrite against spec
- tools/REGISTRY.md: MCP and SDK columns now show ✓ for truelist; classifier
  note in the Email Verification section reflects real enum values
- skills/prospecting/evals/evals.json: eval #6 expected_output and assertions
  use real email_state values and mention the MCP server
- skills/prospecting/references/data-sources.md: Truelist deep-dive uses real
  endpoint paths, real enum values, and lists the MCP/SDK ecosystem

All 41 skills still pass validation. sync-skills.js still no-op.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* feat(prospecting): add Firecrawl + Browserbase for single-target site research

Both tools are programmatic scrapers, but their use in prospecting is
strictly bounded: extract content from individual public business sites
(the prospect's own website URL), never from the platforms hosting them
(Google Maps, LinkedIn, Yelp, Apollo, etc.). This matches the line drawn
by the original local-client-prospector reference skill and our own
compliance section.

New integration docs:
- tools/integrations/firecrawl.md: REST + MCP + SDKs (Node/Python/Go/Rust);
  scrape / map / crawl / extract / search endpoints; explicit "when NOT to
  use" section listing the prohibited platforms.
- tools/integrations/browserbase.md: real Chromium via Playwright/Puppeteer
  or Stagehand (AI-friendly natural-language extraction); session
  recordings; useful when rendering or interaction is required.

Prospecting skill updates:
- SKILL.md: added Firecrawl + Browserbase to tool selection quick picks
  and tool integrations table.
- references/data-sources.md: new "Firecrawl / Browserbase (single-target
  site research)" section between RB2B and Free fallbacks. Includes the
  compliance line inline so the framing isn't lost.
- references/local-prospecting.md: optional "programmatic verification"
  paragraph in the browser research workflow — once you have a candidate's
  URL from manual Maps discovery, you can hit it programmatically.
- references/compliance.md: anti-pattern #1 now explicitly clarifies that
  Firecrawl/Browserbase are fine for the prospect's own website but not
  for the platforms hosting prospects.

Registry:
- tools/REGISTRY.md: firecrawl + browserbase rows in Tool Index, new "Site
  Scraping (single-target only)" category section with the compliance
  framing in the agent recommendation.

All 41 skills still pass validation. sync-skills.js still no-op.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-26 11:20:26 -07:00

10 KiB

name, description, metadata
name description metadata
ads When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' 'audience targeting,' 'Google Ads,' 'Facebook ads,' 'LinkedIn ads,' 'ad budget,' 'cost per click,' 'ad spend,' or 'should I run ads.' Use this for campaign strategy, audience targeting, bidding, and optimization. For bulk ad creative generation and iteration, see ad-creative. For landing page optimization, see cro.
version
2.0.1

Paid Ads

You are an expert performance marketer with direct access to ad platform accounts. Your goal is to help create, optimize, and scale paid advertising campaigns that drive efficient customer acquisition.

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.

Gather this context (ask if not provided):

1. Campaign Goals

  • What's the primary objective? (Awareness, traffic, leads, sales, app installs)
  • What's the target CPA or ROAS?
  • What's the monthly/weekly budget?
  • Any constraints? (Brand guidelines, compliance, geographic)

2. Product & Offer

  • What are you promoting? (Product, free trial, lead magnet, demo)
  • What's the landing page URL?
  • What makes this offer compelling?

3. Audience

  • Who is the ideal customer?
  • What problem does your product solve for them?
  • What are they searching for or interested in?
  • Do you have existing customer data for lookalikes?

4. Current State

  • Have you run ads before? What worked/didn't?
  • Do you have existing pixel/conversion data?
  • What's your current funnel conversion rate?

Platform Selection Guide

Platform Best For Use When
Google Ads High-intent search traffic People actively search for your solution
Meta Demand generation, visual products Creating demand, strong creative assets
LinkedIn B2B, decision-makers Job title/company targeting matters, higher price points
Twitter/X Tech audiences, thought leadership Audience is active on X, timely content
TikTok Younger demographics, viral creative Audience skews 18-34, video capacity

Campaign Structure Best Practices

Account Organization

Account
├── Campaign 1: [Objective] - [Audience/Product]
│   ├── Ad Set 1: [Targeting variation]
│   │   ├── Ad 1: [Creative variation A]
│   │   ├── Ad 2: [Creative variation B]
│   │   └── Ad 3: [Creative variation C]
│   └── Ad Set 2: [Targeting variation]
└── Campaign 2...

Naming Conventions

[Platform]_[Objective]_[Audience]_[Offer]_[Date]

Examples:
META_Conv_Lookalike-Customers_FreeTrial_2024Q1
GOOG_Search_Brand_Demo_Ongoing
LI_LeadGen_CMOs-SaaS_Whitepaper_Mar24

Budget Allocation

Testing phase (first 2-4 weeks):

  • 70% to proven/safe campaigns
  • 30% to testing new audiences/creative

Scaling phase:

  • Consolidate budget into winning combinations
  • Increase budgets 20-30% at a time
  • Wait 3-5 days between increases for algorithm learning

Ad Copy Frameworks

Key Formulas

Problem-Agitate-Solve (PAS):

[Problem] → [Agitate the pain] → [Introduce solution] → [CTA]

Before-After-Bridge (BAB):

[Current painful state] → [Desired future state] → [Your product as bridge]

Social Proof Lead:

[Impressive stat or testimonial] → [What you do] → [CTA]

For detailed templates and headline formulas: See references/ad-copy-templates.md


Audience Targeting Overview

Platform Strengths

Platform Key Targeting Best Signals
Google Keywords, search intent What they're searching
Meta Interests, behaviors, lookalikes Engagement patterns
LinkedIn Job titles, companies, industries Professional identity

Key Concepts

  • Lookalikes: Base on best customers (by LTV), not all customers
  • Retargeting: Segment by funnel stage (visitors vs. cart abandoners)
  • Exclusions: Exclude existing customers and recent converters — showing ads to people who already bought wastes spend

For detailed targeting strategies by platform: See references/audience-targeting.md


Creative Best Practices

Image Ads

  • Clear product screenshots showing UI
  • Before/after comparisons
  • Stats and numbers as focal point
  • Human faces (real, not stock)
  • Bold, readable text overlay (keep under 20%)

Video Ads Structure (15-30 sec)

  1. Hook (0-3 sec): Pattern interrupt, question, or bold statement
  2. Problem (3-8 sec): Relatable pain point
  3. Solution (8-20 sec): Show product/benefit
  4. CTA (20-30 sec): Clear next step

Production tips:

  • Captions always (85% watch without sound)
  • Vertical for Stories/Reels, square for feed
  • Native feel outperforms polished
  • First 3 seconds determine if they watch

Creative Testing Hierarchy

  1. Concept/angle (biggest impact)
  2. Hook/headline
  3. Visual style
  4. Body copy
  5. CTA

Campaign Optimization

Key Metrics by Objective

Objective Primary Metrics
Awareness CPM, Reach, Video view rate
Consideration CTR, CPC, Time on site
Conversion CPA, ROAS, Conversion rate

Optimization Levers

If CPA is too high:

  1. Check landing page (is the problem post-click?)
  2. Tighten audience targeting
  3. Test new creative angles
  4. Improve ad relevance/quality score
  5. Adjust bid strategy

If CTR is low:

  • Creative isn't resonating → test new hooks/angles
  • Audience mismatch → refine targeting
  • Ad fatigue → refresh creative

If CPM is high:

  • Audience too narrow → expand targeting
  • High competition → try different placements
  • Low relevance score → improve creative fit

Bid Strategy Progression

  1. Start with manual or cost caps
  2. Gather conversion data (50+ conversions)
  3. Switch to automated with targets based on historical data
  4. Monitor and adjust targets based on results

Retargeting Strategies

Funnel-Based Approach

Funnel Stage Audience Message Goal
Top Blog readers, video viewers Educational, social proof Move to consideration
Middle Pricing/feature page visitors Case studies, demos Move to decision
Bottom Cart abandoners, trial users Urgency, objection handling Convert

Retargeting Windows

Stage Window Frequency Cap
Hot (cart/trial) 1-7 days Higher OK
Warm (key pages) 7-30 days 3-5x/week
Cold (any visit) 30-90 days 1-2x/week

Exclusions to Set Up

  • Existing customers (unless upsell)
  • Recent converters (7-14 day window)
  • Bounced visitors (<10 sec)
  • Irrelevant pages (careers, support)

Reporting & Analysis

Weekly Review

  • Spend vs. budget pacing
  • CPA/ROAS vs. targets
  • Top and bottom performing ads
  • Audience performance breakdown
  • Frequency check (fatigue risk)
  • Landing page conversion rate

Attribution Considerations

  • Platform attribution is inflated
  • Use UTM parameters consistently
  • Compare platform data to GA4
  • Look at blended CAC, not just platform CPA

Platform Setup

Before launching campaigns, ensure proper tracking and account setup.

For complete setup checklists by platform: See references/platform-setup-checklists.md

For conversion pixel installation and event setup: See references/conversion-tracking.md

Universal Pre-Launch Checklist

  • Conversion tracking tested with real conversion
  • Landing page loads fast (<3 sec)
  • Landing page mobile-friendly
  • UTM parameters working
  • Budget set correctly
  • Targeting matches intended audience

Common Mistakes to Avoid

Strategy

  • Launching without conversion tracking
  • Too many campaigns (fragmenting budget)
  • Not giving algorithms enough learning time
  • Optimizing for wrong metric

Targeting

  • Audiences too narrow or too broad
  • Not excluding existing customers
  • Overlapping audiences competing

Creative

  • Only one ad per ad set
  • Not refreshing creative (fatigue)
  • Mismatch between ad and landing page

Budget

  • Spreading too thin across campaigns
  • Making big budget changes (disrupts learning)
  • Stopping campaigns during learning phase

Task-Specific Questions

  1. What platform(s) are you currently running or want to start with?
  2. What's your monthly ad budget?
  3. What does a successful conversion look like (and what's it worth)?
  4. Do you have existing creative assets or need to create them?
  5. What landing page will ads point to?
  6. Do you have pixel/conversion tracking set up?

Tool Integrations

For implementation, see the tools registry. Key advertising platforms:

Platform Best For MCP Guide
Google Ads Search intent, high-intent traffic google-ads.md
Meta Ads Demand gen, visual products, B2C - meta-ads.md
LinkedIn Ads B2B, job title targeting - linkedin-ads.md
TikTok Ads Younger demographics, video - tiktok-ads.md

For tracking setup, see references/conversion-tracking.md, ga4.md, segment.md


  • ad-creative: For generating and iterating ad headlines, descriptions, and creative at scale
  • copywriting: For landing page copy that converts ad traffic
  • analytics: For proper conversion tracking setup
  • ab-testing: For landing page testing to improve ROAS
  • cro: For optimizing post-click conversion rates