account-research

name	account-research
version	1.0.0
description	Builds a multi-angle profile of a target company — firmographics, decision makers, tech stack, recent posts, and ad spend — by orchestrating enrich_company, lead_search (scoped to that company), web_tech_stack, post_keyword_search, and ad_search. Use when the user wants intelligence on a specific account before outreach, mapping, or a meeting. Proactively invoke on "research Acme", "who should I talk to at X", "tell me about <company>", "account mapping", "decision makers at <company>".
benefits-from	["richapi-gtm","competitive-intel","pre-meeting-briefing"]
allowed-tools	["Bash","Read","Write","Edit","WebFetch","AskUserQuestion"]
triggers	["research <company>","who should I talk to at","tell me about <company>","account mapping","decision makers at"]

account-research

Everything the user needs to know about a target company in one orchestrated pass.

Preamble

~/.claude/skills/richapi-gtm-skills/bin/richapi-skills-preflight

Phase 0 — resolve the account

Input varieties:

• LinkedIn company URL → use directly with enrich_company
• Company name only → run clean_domain (0.5 credits) to get domain, then enrich_company
• Domain only → enrich_company (it accepts either)

If ambiguous (e.g. "Acme" could be 10 different companies), ask which domain/URL.

Phase 1 — firmographic baseline

Call enrich_company (1 credit). Extract:

• Employee count, headcount band, industries
• HQ location, founded year
• Website, LinkedIn URL, company ID
• Specialties, description

Stop and confirm the company match before spending more credits.

Phase 2 — pick research depth

Ask the user — or infer from the prompt — which angles they need:

Angle	Tool	Cost	When to run
Decision makers	lead_search scoped to this company	0.5 / result × ~15 results ≈ 7.5	Always, unless explicitly told not to
Tech stack / GTM signals	web_tech_stack	2	When the user sells to eng/IT or wants GTM intent signals
All-in-one site report	website_intelligence	5	When the user wants "the full picture" — replaces tech_stack + pixels + social + emails
Recent posts	post_keyword_search with fromCompany	6	When the user cares about positioning / recent announcements
Ad activity	ad_search filtered to this company	0.2 / result	When the user wants marketing / GTM intel
Web emails	web_emails	3	Only if direct contacts via email are desired (privacy-sensitive — confirm)

Default depth (no ask): Firmographic + Decision makers. Anything else → ask.

Phase 3 — decision-maker mapping

This is the core GTM output. Use lead_search with:

{
  "currentCompanies": ["<company URL or name>"],
  "seniority": ["Director", "Vice President", "CXO", "Owner / Partner"],
  "page": 1
}

Override the seniority band only if the user specifies (e.g. "I need individual contributors" → drop seniority). If the user wants a specific function:

{ "functions": ["Sales"] }  // or Engineering, Marketing, Product, etc.

Stop at 25 results (1 page = 12.5 credits). If user wants more, paginate with sessionId.

Present as an org map

Group results by function, then by seniority within each function:

Engineering
  ├─ CTO / VP Eng
  │    • Jane Smith — CTO (8yr tenure) — linkedin.com/in/…
  │    • John Liu — VP Engineering (2yr) — linkedin.com/in/…
  └─ Director of Engineering
       • Alex Chen — Director, Platform (1yr) — linkedin.com/in/…
Sales
  ├─ CRO / VP Sales
  │    • Maria Kim — VP of Sales (3yr) — linkedin.com/in/…
…

This is the highest-leverage output — the user should be able to pick their target in 5 seconds.

Phase 4 — optional deeper angles

If the user requested tech stack / posts / ads, run those in parallel (one tool call message, multiple tools). Report each as a separate section.

Tech stack interpretation

web_tech_stack returns category-grouped tech. Highlight:

• Marketing stack (HubSpot, Marketo, Pardot) → implies their GTM maturity
• Analytics (Segment, Amplitude, Mixpanel) → data-driven culture
• CRM (Salesforce, HubSpot, Pipedrive) → integration paths
• Cloud + dev infra (AWS/GCP, Vercel, Cloudflare) → relevant if you sell dev tools
• Security / compliance (Okta, Auth0) → enterprise signals

Post / ad signals

• Look for "we're hiring", "just raised", product launches → buying-signal timing.
• post_keyword_search with fromCompany: <urn> pulls company-page posts; for founder/CEO thought leadership, use profile_activities on the CEO's URN instead.

Phase 5 — synthesize

End with a briefing block, not a wall of JSON:

Acme Corp — snapshot
  Industry: Financial Services  |  Size: 501-1000  |  HQ: New York, NY
  Stack signals: HubSpot + Segment + AWS + Okta → enterprise-grade, growth-stage
  Hiring signals: 12 open eng roles in last 30d → likely scaling platform team

Top decision makers to target
  • Jane Smith — CTO — 8yr tenure, recently posted on platform migration
  • Maria Kim — VP Sales — new to the role (3mo), likely evaluating vendors
  • Alex Chen — Director of Platform — owns cloud budget, active on LinkedIn

Recommended next step
  → enrich-and-verify on these 3 → compose outreach → track in CRM

Cost ceiling

Default total ≤ 15 credits (enrich_company 1 + lead_search 12.5 + web_tech_stack 2 if asked ≈ 15).

If the user wants the full website_intelligence + posts + ads sweep, estimate and confirm (typically 30–50 credits for a complete picture).

Follow-up hooks

After the briefing:

• "Want me to find emails for [Jane, Maria, Alex]? → enrich-and-verify"
• "Want pre-meeting prep on one of them? → pre-meeting-briefing"
• "Want to compare against a competitor? → competitive-intel"

Offer to schedule this

For target-account lists (the user's named ABM list, not one-off research):

"Is this a tier-1 named account? Want me to refresh this monthly so new decision makers + post activity land in your CRM automatically? → scheduled-workflow."

Monthly is the sweet spot for named accounts — firmographic changes don't move weekly, and nothing drifts fast enough to warrant higher frequency.