company-current-gtm-analysis

name	company-current-gtm-analysis
description	Analyze what a target company is doing across every go-to-market dimension — content, founder thought leadership, SEO/traffic, hiring, social, acquisition channels, podcasts/press, reviews, positioning, partnerships — and grade each A–F to expose white space. Run before designing a GTM strategy so the plan fills real gaps. Keyless backbone; the agent grades and writes the report.
metadata	{"version":"1.0.1","category":"competitive-intel","type":"composite"}

Company Current GTM Analysis

Composite: deterministic scripts harvest each GTM channel's public footprint; you, the agent, grade each dimension (A–F), find white space, and write the report.

When to use

• "Run a GTM analysis for [company]." / "What is [company] doing across all of GTM?"
• Before a new client engagement or competitive strategy build.
• When you need a channel-by-channel scorecard plus prioritized white-space opportunities.

How to run

Work the ten dimensions; parallelize the independent fetches.

Content / blog

python3 ${SKILL_DIR}/scripts/fetch_feed.py --url https://company.com/blog \
  --output ${WORKSPACE}/blog_feed.json          # cadence, authors, recent topics
python3 ${SKILL_DIR}/scripts/fetch_pages.py \
  --url https://company.com/blog https://company.com/resources \
  --output ${WORKSPACE}/content_pages.json

Positioning, customers, partnerships, integrations, careers

python3 ${SKILL_DIR}/scripts/fetch_pages.py \
  --url https://company.com https://company.com/about https://company.com/customers \
        https://company.com/pricing https://company.com/integrations \
        https://company.com/partners https://company.com/careers \
  --output ${WORKSPACE}/gtm_pages.json

Pages with stats.likely_js_rendered: true (JS ATS boards, JS marketing sites): re-fetch with node ${SKILL_DIR}/scripts/render_page.mjs --url <u> --output ....

SEO / traffic

Use the seo-traffic-analyzer skill (keyless serp + SimilarWeb) for this section, or do site: probes with your own web search. Do not invent traffic numbers.

Founder LinkedIn, social, podcasts/press, reviews

• Founder LinkedIn posts: render a profile with render_page.mjs --url <profile> --wait 6000 for a one-off, or use PHANTOMBUSTER_API_KEY (+ LinkedIn cookie) for scale. If neither, mark the section "[NEEDS VERIFICATION]".
• Social/podcasts/press: your own web search per platform; render specific pages as needed.
• Reviews: render_page.mjs on the G2/Capterra review URL (anti-bot, JS) — see Notes for the Apify fallback.

Synthesize (you, the agent — no script)

Read all collected JSON and write current-gtm-analysis.md: executive summary, ten dimension sections, and an A–F scorecard across ~15 dimensions, each graded with evidence and the biggest opportunity. Grade relative to company stage. White space = impact × effort. Save to ${WORKSPACE}/ and post as a channel attachment.

Outputs

• ${WORKSPACE}/blog_feed.json, gtm_pages.json, content_pages.json — collected signal.
• ${WORKSPACE}/current-gtm-analysis.md — the graded report (your synthesis).

Credentials / env

• Required: none — fetch/feed/render scripts are keyless; grading is the agent.
• Optional: PHANTOMBUSTER_API_KEY (+ LinkedIn cookie) for founder-LinkedIn at scale; APIFY_API_TOKEN for deeper Reddit/YouTube/review/LinkedIn scraping; SUPABASE_URL/SUPABASE_KEY or AIRTABLE_API_KEY for run history; DATAFORSEO_LOGIN/DATAFORSEO_PASSWORD or SERPER_API_KEY for the per-channel discovery searches (if set -> paid SERP; if not -> the agent's own web search, the default). Semrush/ Ahrefs have no Robomotion package — if the team has a key, treat as optional manual enrichment.

Notes & edge cases

• Parallelize the independent research threads to cut wall-clock time.
• If fetch_pages.py returns empty (likely_js_rendered), fall back to render_page.mjs.
• Grade relative to stage — a seed startup needs no analyst coverage; a Series-A does.
• Never invent metrics; flag unverifiable items "[NEEDS VERIFICATION]".
• Founder-LinkedIn underinvestment is usually the #1 finding — surface it explicitly when true.
• Apify degrade (when set): curl -s "https://api.apify.com/v2/acts/<actor>/run-sync-get-dataset-items?token=$APIFY_API_TOKEN" -d '{...}'.