---

name: plan-gtm description: > Plan-only GTM audit: monetization, positioning, activation funnel, SEO/AEO, distribution, and a founder interview. Use when "GTM", "go-to-market", "get more users", "grow traffic", or "should this be freemium". Execute → workflow-gtm. license: MIT effort: high

plan-gtm — Go-to-market audit + interview + plan

Degree of freedom: MIXED. Repo inventory greps and the interview rules [LOW freedom — run exactly]; positioning, model fit, and channel choice [HIGH freedom]. Stay plan-only: no copy, pricing, route, or license edits until the founder approves a phase.

Role: Growth lead who reads code. The repo already tells you how the product is sold; the founder tells you who it is for and what "growth" means this quarter. Neither alone is a strategy.

Task: Inventory the repo, interview the founder, diagnose the gap between how the product is marketed and how it should be, emit plan-gtm.md with a phased burndown mapped to execution skills. Change nothing until approved.

This skill vs neighbors

Skill	Owns
plan-gtm (this)	Strategy: who, why-us, how-paid, which channels, what to measure
workflow-gtm	Executes the approved phases in order
plan-pricing	Value metric, tiers, price points — after this skill picks the model
enhance-web-conversion	Hero, pricing page, upgrade prompts (apply)
enhance-onboarding	First-session activation (apply)
enhance-lifecycle-email / enhance-growth-loops	Nudges and loops (apply)
docs-launch-kit / docs-comparison-pages	Launch posts; "X vs Y" pages (apply)
audit-registry-listing	README / npm / GitHub surface for repo-as-product
iterate-gtm-weekly	The weekly loop after Phase 4
enhance-web-seo / plan-aeo-readiness	Classic search / AI-engine citation
audit-analytics	Whether the funnel is instrumented at all
plan-aso	App Store / Play listing (mobile)
design-prd	What to build next — not how to sell what exists
workflow-grilling	Generic interview; this skill uses its rules on GTM questions

Do not fire for "write the landing page" (→ enhance-web-landing) or "why is my SEO bad" alone (→ enhance-web-seo).

How to reason (every finding)

1. Observe — quote the file, route, or copy that shows how the product is sold today
2. Interpret — what a first-time visitor and a first-time user actually experience
3. Classify — positioning / model / activation / discoverability / distribution / measurement
4. Decide — keep, tune, or switch; one execution skill; one metric that proves it

Worked example

Observe: LICENSE is MIT; README hero says "145 skills"; /pricing route absent; posthog.init in layout.tsx; no activated event; 3.6k npm downloads, 9 GitHub stars. Interpret: free forever with no ask; visitors count features, not outcomes; installs happen, nobody comes back or bookmarks. Classify: positioning (feature-count hero) + measurement (no activation event) + distribution (install ≠ retained). Decide: tune — lead the hero with the completion-gate outcome (enhance-web-conversion); define activated = first skill run in a real repo (enhance-onboarding + audit-analytics); monetization stays free until activation is measured. Metric: activated installs / week.

Self-critique before the burndown [LOW freedom — do not skip]

1. evidenced-not-assumed — every inventory row cites file:line, a route, or a number the founder supplied; "unmeasured" is written where no number exists
2. decisions-are-theirs — monetization model, license, ICP, and budget came from the interview log in the founder's words, not from your recommendation
3. one-metric — the plan names one north-star and one activation event
4. two-channels-max — no plan lists five channels; each carries its caveat
5. plan-only — no copy, pricing, route, robots, or license edits
6. honest-growth — no fake scarcity, upvote rings, fabricated testimonials, or analytics before consent anywhere in the plan
7. right-owner — each phase hands to exactly one execution skill

---

Step A — Repo inventory [LOW freedom — run exactly]

Grep before you ask. Record evidence per row.

Area	Signals to grep / open	What it tells you
Monetization	stripe, paddle, lemonsqueezy, polar, revenuecat, react-native-purchases; /pricing route; plan|tier|isPro|premium|entitlement|paywall|subscription; FUNDING.yml, sponsor links; ee/ or enterprise/; docker-compose + self-host docs	free / freemium / trial (opt-in vs card) / usage / open-core / hosted / donation
License	LICENSE header: MIT/Apache vs AGPL vs BSL/FSL/Elastic	permissive = adoption play; AGPL + commercial = open-core; source-available = cloud-defence, not OSI
Positioning	README H1 + first paragraph; landing <h1>; <title>, meta description, OG title	outcome vs feature-count; who it names; category it claims
ICP signals	docs audience, i18n locales, currencies, example data, screenshots	who the product already assumes
Activation path	/signup, /login, auth providers (OAuth / magic link / password); onboarding, welcome, getting-started, checklist, sample, template, empty states; steps between landing and first value	time-to-value in steps; signup wall before any value?
Analytics	posthog, @amplitude, mixpanel, gtag, plausible, umami, @vercel/analytics; track(, capture(; consent banner	is Visit→Signup→Activated→Paid measurable; consent-gated?
SEO / AEO	robots.txt, sitemap*, llms.txt, per-page title/description, JSON-LD, canonical, /blog, /docs, comparison pages	can search and answer engines find and cite it (baseline only — deep audit is enhance-web-seo / plan-aeo-readiness)
Distribution assets	README badges/hero image, CHANGELOG.md, publishConfig / PyPI, GitHub topics + stars, Product Hunt / HN / awesome-list links, newsletter, Discord/Slack, social handles	where it is already listed; what a share looks like
Trust	testimonials, logos, security/privacy/terms pages, status page, real screenshots	why a stranger would believe the claim
Numbers	npm/PyPI downloads, stars, store installs, analytics dashboards	fill in; otherwise write unmeasured

Output an Inventory table — Area | Current state | Evidence | Gap?.

Step B — Founder interview [LOW freedom — rules; HIGH freedom — depth]

Rules from workflow-grilling: one question per turn, recommend an answer with each, facts from the repo are never asked, log decisions in the founder's words. Walk the ladder in order; skip rungs the inventory already answered.

1. 90-day goal metric — recommend: activated users per week (pre-revenue) or MRR (post-revenue). Not stars, not upvotes.
2. Who exactly — role + situation + what they use today instead. Recommend the ICP the inventory implies.
3. Current numbers and channels — visits, signups, activation, paid, where the last spike came from. Ask for the dashboard or CSV.
4. Monetization intent — stay free / freemium / trial / usage / open-core / hosted. Recommend from the model-fit table below; the choice is theirs.
5. Budget — hours per week and money per month for growth work.
6. Geography and language — which market first (e.g. JP vs EN).
7. Alternatives — the three things a buyer compares against.
8. Constraints — brand, legal, store policy, team, "never do X".

Stop when the plan can be written. Close with the decision log. If the signup form has no "how did you hear about us" field, propose one in Phase 1 — it is the cheapest channel attribution that exists.

Step C — Diagnose [HIGH freedom]

Positioning (Dunford order — do not start at category)

competitive alternatives → unique attributes → value those attributes enable → best-fit customers who care most → market category that makes it obvious. Write one sentence: For [ICP] who [situation], [product] is the [category] that [value], unlike [alternative]. The hero, README first line, and meta description must all be able to carry it.

Monetization model fit

Free-to-paid, 2026 (ChartMogul × Kyle Poyar × ProductLed, ~200 self-serve products):

Model	Good	Great	Fits when	Repo signals
Freemium	3–5%	8–12%	volume + network/viral loop; low marginal cost	free tier limits in code, isPro gates
Freemium, ungated (no account to try)	7–9%	8–12%	adoption is the goal; value visible in one session	demo mode, sample data, no auth on core route
Free trial, no card	4–6%	10–15%	B2B, value needs setup time	trialEndsAt, 14-day default
Free trial, card required	25–35%	50–60%	intent over volume; ACV justifies friction	Stripe Checkout before app
Reverse trial	4–6%	8–12%	not statistically better than the two above	premium-then-downgrade logic
Usage-based / hybrid (credits)	—	—	cost per action (AI, infra); expansion via usage; now 41% of B2B SaaS	metering tables, credits, Stripe metered prices
Open-core + hosted cloud	0.5–2% self-host → paid; cloud carries 48–73% of revenue at public OSS vendors	—	painful to operate; enterprise SSO/RBAC/audit	AGPL + ee/, docker-compose, cloud signup
Donation / sponsorship	—	—	libraries and CLIs with no hosted surface; rarely sustains alone	FUNDING.yml, no billing code
Paid-only	—	—	niche pro tool, strong word of mouth	paywall before any value, no free plan

Median across all models is 8%; a fifth of products convert under 2.5%. "Freemium vs trial" is the wrong question: adoption → open the product before signup; conversion → require a card. Activation inside the free window explains most of the variance — fix activation before changing price. Underpricing attracts the curious, not the committed. Never recommend a license change as a growth tactic; relicensing cost Elastic and Redis contributors and gained no revenue. Full rows and URLs: references/benchmarks-2026.md.

Activation and north-star

Reforge order: Setup (must-have info) → Aha (core value once) → Habit (core action at its natural frequency). activated is the aha event — not signup, not tour end, never payment (that kills it as a leading indicator). A valid activation event shows ≥ 2× retention for users who hit it; if analytics exist, pick the event combination that best predicts 3-month retention. Benchmarks: median B2B activation 37% (good = p60, great = p80 for the product type); below 20% is a broken first session; time-to-value over 24 h collapses activation under 25%; day-7 return ≥ 7% of a new cohort is top quartile. Only about a third of PLG companies track activation at all — an "unmeasured" cell here is finding #1. Map the funnel Visit → Signup → Activated → Habit → Paid → Refer with a number or unmeasured in each cell; group by organization for B2B.

Channels — pick ≤ 2 primary + 1 loop

Channel	Best for	Caveat
Show HN	dev tools, OSS, infra	front page = 5–30k visits, 50–400 signups; >10 points only ~11% of posts; runnable thing, no signup wall, sober human-written post, answer every comment for 2 h
Product Hunt	consumer, design-led SaaS	featured rate ~10%; 1–2% visit→signup for B2B; credibility artifact, not acquisition; relaunch per major version
Reddit / niche communities	narrow ICP, B2B	value-first threads; link-only posts die
Content + comparison pages	anything searched	"X vs Y" / "alternatives to" pages took 78% of clicks from 28% of pages in one test; honest, current, unique per page — scaled AI pages are a Google spam-policy hit
AEO / answer engines	anything explained	earned third-party mentions earn ~6.5× more citations than owned pages; llms.txt has zero Search effect but coding assistants read it on docs sites → plan-aeo-readiness
Registries & directories	npm/PyPI packages, skills, plugins, extensions	discovery happens in the registry; README first 10 lines are the hero
Community (Discord/GitHub Discussions)	OSS, dev tools	retention and word-of-mouth, slow to start
Loops	all	"powered by" badge (0.5–3% conversion, near-100% exposure), templates users share, referral credit (SaaS referral rate ~4.75%); value before signup lifts referred conversion 2–5×

Launch is a cadence, not an event: every meaningful release gets a post. Name one distribution hypothesis in the plan — the failure mode is having none, not picking the wrong one.

Onboarding, pricing page, trust

Note gaps only; the fixes belong to enhance-onboarding and enhance-web-conversion. Copy that reads generated → plan-antislop.

Name the failure mode

Every finding maps to one: building before validating (43% of shutdowns are PMF), generic hero, underpricing, no distribution hypothesis, activation untracked or defined as payment, AI-generated content at scale, launching once, reverse trial / AI credits as a fix. The list with sources is in references/benchmarks-2026.md.

Step D — Emit plan-gtm.md, end the turn [LOW freedom — run exactly]

# GTM Plan — <product>

_Plan-only. Nothing changes until each phase is approved._

## Decision log (founder's words)
- Goal metric (90 d): …
- ICP: …
- Monetization: …
- Budget: … h/week, … /month
- Market/language: …

## Inventory verdict
| Area | Status | Worst gap | Evidence |
|------|--------|-----------|----------|

## Positioning statement
For … who …, <product> is the … that …, unlike ….

## Monetization verdict
keep / tune / switch — why, with the benchmark row it is judged against.

## Activation & north-star
- `activated` = …   · north-star = …
| Visit | Signup | Activated | Habit | Paid | Refer |
|-------|--------|-----------|-------|------|-------|
| n | n | unmeasured | … | … | … |

## Channel plan (≤2 + loop)
| Channel | Why this ICP | Caveat | First action |

## Findings
| # | Area | Gap | Evidence | Sev | Direction |

## Phased burndown
- **Phase 1 — Measure & message** → `audit-analytics`, `enhance-web-conversion` (hero), `enhance-readme`; repo-as-product adds `audit-registry-listing`
- **Phase 2 — Activate** → `enhance-onboarding`, `audit-ui-states`, `enhance-web-forms`, `enhance-lifecycle-email` (activation nudges)
- **Phase 3 — Be found** → `enhance-web-seo`, `plan-aeo-readiness`, `docs-comparison-pages`
- **Phase 4 — Launch & loop** → `docs-launch-kit`, `enhance-growth-loops`, `iterate-gtm-weekly`
- **Phase 5 — Monetize** → `plan-pricing` (approve first), `enhance-web-conversion` (pricing, upgrade prompts), `enhance-lifecycle-email` (trial expiry), `audit-payment-system`

## 30 / 60 / 90
| Day | Metric | Target | Owner skill |

## Weekly GTM review (after Phase 4)
Funnel by source · activation cohort · top drop-off step · one experiment
shipped · one launch or post.

## Execution handoff
Approve a phase → `workflow-gtm` runs it and re-reads the funnel table.

End the turn with a standalone recap in chat: the decision log in one line, the two or three highest-impact findings, and Phase 1's first action. The file is the deliverable — write it before the recap.

Guardrails

• Plan only. Inventory + interview + document.
• Unmeasured is a value. Never invent a conversion rate or traffic number.
• No promised outcomes. Rank, virality, and "10x signups" are not deliverables.
• No dark patterns. No fake scarcity, hidden cancel, confirm-shaming, upvote solicitation, fabricated reviews, or analytics before consent.
• Business decisions stay with the founder. Model, price, license, ICP.

Chains with

• workflow-gtm — executes the approved phases.
• Growth gate — pairs with plan-aeo-readiness, plan-aso in docs/PLAN-LOOPS.md.
• audit-analytics — run first when the funnel table is all "unmeasured".
• iterate-gtm-weekly — the weekly loop after Phase 4 (iterate-post-launch keeps production bugs).

Plan at high effort. Execute after approval at the default effort under approved-plan-execution.mdc (no reward hacking, no feature deletion).