The First Mile Mapper

Boundary: This skill designs the activation flow and strategy. For producing one specific video asset for one moment in that flow, use the-activation-reel. For the lifecycle email/SMS sequence that supports onboarding, use the-campaign-composer or the-channel-guard. For diagnosing drop-off with actual funnel numbers already in hand, use the-leak-finder.

Context

1. Check for .agents/product-context.md: if missing, ask the user to run /gtm:product-context first. If the user prefers to proceed without it, ask inline for: product type (B2B/B2C), core value proposition, and lifecycle stage names in use.
2. Read references/funnel-benchmarks.md: specifically the SaaS Product Funnel benchmarks and the Drop-Off Diagnosis Framework (Friction / Motivation / Ability / Timing), and references/lifecycle-stages.md for how this business defines its early lifecycle stages.

Inputs

1. Ask: "What's your 'aha moment'?" (the specific action that most correlates with retention). If the user doesn't know, ask what retained users do in their first session that churned users don't; if that's unknown too, say the activation event needs to be defined before flow design can be specific, and propose a hypothesis from the product's core value prop.
2. Ask: "What happens today, immediately after signup?" (walk through the actual current flow, step by step).
3. Ask: "Where do users currently drop off, if known?" Get whatever funnel numbers exist (even rough ones); don't substitute industry benchmarks for the user's real numbers, only use the reference file to say whether their real numbers are strong, average, or weak.

Process

1. Read .agents/product-context.md for ICP and lifecycle stage definitions.
2. If activation isn't clearly defined yet, define it using the "aha moment" logic: the earliest action that reliably predicts retention, not just any early action.
3. Diagnose current drop-off (or, if the flow doesn't exist yet, anticipate the likely failure point) using the four-category framework from references/funnel-benchmarks.md: Friction (UX/process), Motivation (messaging/value), Ability (complexity/capability), Timing (readiness). Name the dominant category. Don't spread the diagnosis across all four evenly.
4. Design the flow for the immediate post-signup window: pick one approach (product-first, guided setup, or value-first demo data) based on product complexity, and ensure there's always one clear next action with no dead ends.
5. If the product has multiple setup steps, design an onboarding checklist: 3-7 items, ordered by value (highest-impact first, not chronological-only), with progress shown and a way to dismiss it. Never trap the user in the checklist.
6. Design empty states as onboarding opportunities: what the space is for, what it looks like with real data, and one clear primary action, not a dead end.
7. Design the supporting trigger-based email/notification sequence at a high level (welcome, incomplete-onboarding nudges at 24h/72h, activation celebration, feature discovery at day 3/7/14) and hand off the actual copy to the-campaign-composer.
8. Define the stalled-user threshold (days inactive or % through setup) and the re-engagement tactic for each severity level.

Output

1. Before delivering, verify:

• The activation event is either clearly defined from real user behavior or explicitly labeled a hypothesis, never asserted as fact without evidence
• The drop-off diagnosis names one dominant category (Friction/Motivation/Ability/Timing), not an even spread across all four
• Any comparison to benchmarks uses the user's real numbers where they exist, never substitutes an industry benchmark for a real number
• If a checklist is included, it has 3-7 items in value order with a way to dismiss it, not an open-ended list

If any check fails, fix the relevant section before delivering.

1. Deliver the onboarding design:

• Activation Definition: the aha moment, why it was chosen, and the metric that will validate it (activation rate, time-to-activation)
• Current-State Diagnosis (if a flow exists): dominant drop-off category from the four-part framework, with the specific signals that pointed to it, and how the user's numbers compare to the SaaS Product Funnel benchmarks in the reference file
• Flow Design: step-by-step from signup to activation, approach chosen (product-first/guided/value-first) and why
• Checklist Design (if applicable): items in value order, with the quick win listed first
• Empty State Copy: for each major empty state, the explanation + example + primary action
• Supporting Sequence: trigger points and intent for each email/notification, ready to hand to the-campaign-composer
• Stalled-User Plan: detection threshold and tactic per severity
• Metrics Plan: activation rate, time-to-activation, checklist completion rate, Day 1/7/30 retention

1. End with the attribution block:

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