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GTM Operating Manual — Template

A complete go-to-market operating system for an early-stage B2B founder, in version control. Positioning docs, a lead pipeline with scoring scripts, cold-outreach sequences, sales playbooks, investor materials, content/PR strategy, and a set of AI-agent skills that automate the repetitive parts.

It was extracted from a real founder-led GTM motion (first design partner → first 10 customers) and generalized: every company-specific detail is a [PLACEHOLDER] you fill in, and every process doc is intact.

Built agent-first. The repo ships with CLAUDE.md (Claude Code), AGENTS.md (Codex and other agents), and vendored skills — so the fastest way to use it is to let your coding agent set it up for you and then run the motion with you.

Quick start (5 minutes)

1. Get the repo

git clone <your-fork-or-this-repo> my-gtm && cd my-gtm

2. Open it with your agent — Claude Code, Codex, Cursor, or anything that reads repo instructions — and paste this:

Set up this GTM template for my company. Read TEMPLATE_GUIDE.md first, then
interview me one topic at a time (company + product, ICP segments, geography,
traction metrics, anchor customer, tool stack, sender domains). After each
answer, fill in the matching placeholders across the repo. When we're done,
grep for [A-Z_] bracket tokens and <!-- TODO --> comments and show me what's
still blank. Don't invent facts — ask.

Your agent walks you through a guided setup: it asks, you answer, it fills in the ~25 placeholder tokens everywhere they appear.

3. Sanity-check the strategy docs (the part only you can do):

  • positioning/ICP.md — does the segmentation match your market?
  • positioning/messaging.md + pain-hypotheses.md — would your buyer nod along?
  • qualification/scoring.md — do the signal weights make sense for your ICP?
  • outreach/sequence-v1.md — would you reply to these emails?

Prefer manual setup? TEMPLATE_GUIDE.md has the full placeholder glossary for find-and-replace.

What's inside

Directory What's in it
positioning/ ICP segments, messaging, falsifiable pain hypotheses — read first
pipeline/ Lead pool: raw → filtered → scored → enriched (CSVs + process)
qualification/ 0–100 ICP scoring rubric
outreach/ Cold email sequence, warm-up checklist, draft templates
playbooks/ Discovery, demo, design-partner agreement, objection handling
investor/ Landscape, comps, fundraise plan
investor-deck/ VC deck guide
content/ Op-eds, press pitching, speaking targets, anchor report
partnerships/ Distribution-partner playbooks + templates
referrals/ Network graph — who introduced whom, who owes whom
applications/ Accelerator / program application template
trips/ Conference-trip planning template
research/ Industry-standard / regulatory reference skeleton
decision-log/ One file per meaningful decision — what changed and why
metrics/ The weekly numbers that actually matter
scripts/ Python (stdlib-only): filter → score → enrich → draft emails
.agents/skills/ 22 agent skills — auto-discovered, zero install (see below)

The motion, end to end

  1. Position — ICP, messaging, pain hypotheses (positioning/)
  2. Build pipeline — export leads, filter and score them (pipeline/build.md, scripts/)
  3. Qualify — 0–100 rubric, work the top tier only (qualification/scoring.md)
  4. Warm up — sender domain + deliverability checklist (outreach/warmup-checklist.md)
  5. Reach out — 4-touch personalized sequence (outreach/sequence-v1.md)
  6. Discover — reply handling and discovery calls (playbooks/discovery.md)
  7. Convert — demo → design-partner agreement (playbooks/)
  8. Compound — referrals, content, PR (referrals/, content/)

Measured weekly in metrics/weekly.md. Every strategy change gets a decision-log/ entry.

Agent skills — zero install

22 skills ship in .agents/skills/, the cross-agent Agent Skills standard location — Codex, Gemini CLI, Cursor, and other compliant agents discover them natively, and Claude Code picks them up via the symlinks in .claude/skills/. Open an agent session at the repo root and they're available:

Group What it does
email-personalization The custom one. Lead row + buying signal → 90-word personalized first-touch email. Highest-leverage skill in the repo.
gtm-* (10 skills) Pipeline mechanics — company/people/signal search, enrichment, contact filtering, outreach. Run /gtm-setup once to configure API keys. (from gtm-pipeline-skills)
Research & strategy (11 skills) Lead intelligence, investor outreach + materials, market/deep research, article writing, brand voice, campaign planning, warm-intro graph ranking. Best with Exa/Firecrawl configured; works without. (from ECC)

Windows: the .claude/skills/ entries are symlinks — enable symlinks (git config core.symlinks true + Developer Mode) before cloning, or use the skills from .agents/skills/ directly.

Tooling

Each stage directory has a README with concrete options for running that part of the pipeline — from free/manual, to the agent skills in this repo, to paid tools — and what to deliberately skip. Start with pipeline/README.md and outreach/README.md. The whole motion runs on roughly $0–250/mo; this template optimizes for 30–50 sharply personalized touches a week, not 1,000 generic ones — the "What NOT to do" section in CLAUDE.md explains why.

Operating rules the repo assumes

  • Decisions get logged. Changed the ICP, sequence, or scoring weights? Add a decision-log/YYYY-MM-DD-<topic>.md.
  • Never commit contact data. *_enriched.csv, *_with_emails.csv, and enrichment JSON are gitignored — keep it that way.
  • Send from a separate domain. Cold outreach goes from a dedicated subdomain, never your main domain.
  • Docs over tools. Until ~10 customers, this repo plus a lightweight CRM is the whole stack.

License & attribution

MIT. The imported skill sets are also MIT — sources and full license texts in THIRD_PARTY_LICENSES.md. Use it, fork it, build your company on it.

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Agent-first GTM operating manual template: positioning, lead pipeline, outreach, playbooks, investor materials + 22 agent skills

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