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Get Started Free →Interview the user once and write a docs/gtm-cofounder/founder-brief.md that every other skill reads first, so the advice is about their real business, not a textbook. Use this before anything else, or whenever the agent lacks context on the user's product, ICP, market, or stage, or is giving generic GTM advice.
.claude/skills/aidevgtm-start-here/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 48% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 188% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 55% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 157% | 0% |
| case-21 | ✗→✓ | ▲ Improved | 159% | 0% |
> Every other skill is only as sharp as what the agent knows about your business. This is that context. Do it once, and every skill after it gets personal.
Use this when: it's your first time here, or the advice you're getting feels generic and textbook because the agent doesn't actually know your product, your users, or your stage.
Answer five core questions and the agent writes a docs/gtm-cofounder/founder-brief.md in your project, enough to give you a real diagnosis and a roadmap in minutes. Everything else is optional and answered as you go: each skill pulls the deeper questions it actually needs, when it needs them, and tells you what answering unlocks. So you start seeing value fast, and the brief gets richer the more you use it, instead of facing a wall of questions on day one.
And the part that matters most: separate what you have validated (a real user who is not your friend told you) from what you are assuming (your best guess for now). Assumptions are completely fine to start with. They just get sent to talk-to-users to become real, so you never build a beautiful go-to-market on a guess.
strategy-and-roadmap. The founder should get a diagnosis and a next move before they answer anything optional.[validated] or [assumption].talk-to-users as the highest-priority next step.strategy-and-roadmap, or ask the founder what they want to tackle. Offer, never impose.Before asking anything, check whether you're running inside the founder's repo. If you are, do a quick, bounded scan first, so the interview sharpens instead of starting cold:
docs/ intro: what the project claims to do, and how they currently describe it.package.json, pyproject.toml, go.mod, and the like): language, dependencies, what it integrates with.This is a quick scan, not an audit. Do not read code line by line, crawl the whole history, or pull anything sensitive. Draft the brief from what you find and tag those facts [validated], they come from real artifacts, not a guess.
Two cautions:
talk-to-users.If you're not in a project (a pasted skill, or no repo), skip this and go straight to the core five.
This is the whole required intake. Answer these and the agent can already diagnose and plan. If you already scanned the repo, don't ask these cold: confirm or refine what you inferred, and spend your questions on what the artifacts can't tell you, the ICP, the buyer, and whether anyone will pay.
Skip these to start. Each skill asks for the ones it needs, when it needs them. Every question says what answering it unlocks, so you only invest where you want the payoff.
Positioning and story
Buyers and pricing
Distribution and motion
Focus
Evidence (be honest, this is the whole point)
Save the answers to docs/gtm-cofounder/founder-brief.md in the founder's project (create the docs/gtm-cofounder/ folder if it does not exist), using the template in this repo (founder-brief.template.md). Keep the [validated] / [assumption] tags on each answer. This file is the shared memory for every other skill. Write it in plain, human prose, with no em-dashes (use commas, colons, or periods), so it never reads as machine-generated.
Lead the brief with the strongest asset (core question 5) at the very top, so the single most powerful thing this founder has anchors every downstream skill. Founders routinely bury it under modesty or detail. As deeper questions get answered over time, add them to the brief under their category.
The brief is a living document, not a form you fill once and forget. Every time the founder learns something real from a user (a talk-to-users call, a lost deal, a piece of feedback), update the relevant line and flip its tag from [assumption] to [validated]. A brief that is mostly [validated] is a company that knows itself. And run market-scan periodically to refresh what has changed outside the brief: a rival's rebrand, a new entrant, a shifted category.
[validated] or [assumption].docs/gtm-cofounder/founder-brief.md in your project so your agent reads it.01-strategy-and-roadmap to get your diagnosis and first move. Don't answer the optional questions yet.Built from real dev-tool GTM experience, with frameworks from Adam Frankl (The Developer-Facing Startup) and Jakub Czakon (markepear.dev). When a framework can't make the call, that's what a human is for: The DevTool GTM Company.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 16,714 | 4,960 | -70% | 1 | 1 | 0% | 2,557 | 2,751 | +8% | 0 | 0 | — |
case-02 | fail→fail | 13,339 | 6,948 | -48% | 1 | 1 | 0% | 1,861 | 2,574 | +38% | 0 | 0 | — |
case-03 | fail→fail | 12,308 | 7,304 | -41% | 1 | 1 | 0% | 1,893 | 2,586 | +37% | 0 | 0 | — |
case-04 | fail→fail | 18,259 | 18,497 | +1% | 1 | 1 | 0% | 2,796 | 4,793 | +71% | 0 | 0 | — |
case-05 | fail→fail | 7,287 | 5,427 | -26% | 1 | 1 | 0% | 355 | 2,734 | +670% | 0 | 0 | — |
case-06 | fail→fail | 36,837 | 20,570 | -44% | 1 | 1 | 0% | 5,215 | 3,903 | -25% | 0 | 0 | — |
case-07 | fail→pass | 14,278 | 8,746 | -39% | 1 | 1 | 0% | 2,376 | 3,506 | +48% | 0 | 0 | — |
case-08 | pass→fail | 11,550 | 8,698 | -25% | 1 | 1 | 0% | 1,671 | 3,383 | +102% | 0 | 0 | — |
case-09 | fail→pass | 8,107 | 4,409 | -46% | 1 | 1 | 0% | 987 | 2,844 | +188% | 0 | 0 | — |
case-10 | fail→fail | 8,057 | 7,732 | -4% | 1 | 1 | 0% | 1,212 | 3,213 | +165% | 0 | 0 | — |
case-11 | pass→pass | 12,283 | 9,097 | -26% | 1 | 1 | 0% | 1,839 | 3,395 | +85% | 0 | 0 | — |
case-12 | fail→pass | 12,194 | 4,036 | -67% | 1 | 1 | 0% | 1,793 | 2,778 | +55% | 0 | 0 | — |
case-13 | pass→pass | 9,524 | 4,791 | -50% | 1 | 1 | 0% | 1,470 | 2,786 | +90% | 0 | 0 | — |
case-14 | fail→pass | 7,833 | 8,868 | +13% | 1 | 1 | 0% | 1,290 | 3,311 | +157% | 0 | 0 | — |
case-15 | pass→pass | 11,146 | 9,816 | -12% | 1 | 1 | 0% | 1,478 | 3,456 | +134% | 0 | 0 | — |
case-16 | fail→fail | 9,867 | 12,284 | +24% | 1 | 1 | 0% | 1,566 | 4,105 | +162% | 0 | 0 | — |
case-17 | fail→fail | 12,352 | 3,034 | -75% | 1 | 1 | 0% | 1,534 | 2,642 | +72% | 0 | 0 | — |
case-18 | pass→pass | 19,275 | 8,383 | -57% | 1 | 1 | 0% | 1,800 | 3,035 | +69% | 0 | 0 | — |
case-19 | pass→pass | 7,269 | 5,747 | -21% | 1 | 1 | 0% | 1,076 | 3,227 | +200% | 0 | 0 | — |
case-20 | pass→pass | 7,468 | 6,228 | -17% | 1 | 1 | 0% | 1,169 | 3,003 | +157% | 0 | 0 | — |
case-21 | fail→pass | 7,832 | 4,577 | -42% | 1 | 1 | 0% | 1,106 | 2,864 | +159% | 0 | 0 | — |
case-22 | fail→pass | 14,826 | 5,486 | -63% | 1 | 1 | 0% | 2,149 | 2,864 | +33% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 20 counted toward the lift figure. The other 2 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +23 percentage points is the difference between those two pass rates over the 20 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.