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event4u-app/agent-config/src/skills/activation-design/SKILL.md

activation-design

Use when defining or auditing the activation event — aha-moment selection, retention correlation, falsifiable definition. Triggers on 'what is our aha moment', 'redefine activation'.

Source repository stars
7
Declared platforms
0
Static risk flags
0
Last source update
2026-07-28
Source checked
2026-07-28

Decision brief

What it does—and where it fits

Triggers on 'what is our aha moment', 'redefine activation'.

Best for

  • The activation event is "signed up" or "logged in" and the funnel looks healthy while retention sinks — the event does not correlate with paid or D30, so the metric is a vanity surface.
  • A new segment is being routed against an activation event built for a previous segment — the aha moment differs by segment and the metric needs to be re-keyed.
  • A product loop redesign needs activation to complete the loop's first cycle (handover from retention-loops) — the activation event must match the binding loop's first reward, not an arbitrary product step.

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/activation-design"
Safe inspection promptEditorial

Inspect the Agent Skill "activation-design" from https://github.com/event4u-app/agent-config/blob/0adf49a8ae84b0ff6e2de8759eea43257e020eff/src/skills/activation-design/SKILL.md at commit 0adf49a8ae84b0ff6e2de8759eea43257e020eff. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Procedure

    Inspect the existing definition. Verify by computing correlation between the event and paid conversion / D30 retention on the trailing four cohorts. If r 0.4 but the event is downstream of paid, it is lagging and useless for in-funnel decisions.

    Is in-product, in-instrumentation, in-segment-shape. NoSits upstream of paid in the funnel. Activation thatMaps to the segment's switch-event. The candidate is the
  2. 02

    Step 0: Inspect — name the current activation event and its correlation

    Inspect the existing definition. Verify by computing correlation between the event and paid conversion / D30 retention on the trailing four cohorts. If r 0.4 but the event is downstream of paid, it is lagging and useless for in-funnel decisions.

    Inspect the existing definition. Verify by computing correlation between the event and paid conversion / D30 retention on the trailing four cohorts. If r 0.4 but the event is downstream of paid, it is lagging and useles…
  3. 03

    Step 1: Generate three candidate activation events

    Each candidate is one observable user action that:

    Is in-product, in-instrumentation, in-segment-shape. NoSits upstream of paid in the funnel. Activation thatMaps to the segment's switch-event. The candidate is the
  4. 04

    Step 2: Compute correlation per candidate

    For each candidate, compute on the trailing four cohorts:

    Correlation with paid conversion (point-biserial r).Correlation with D30 retention among paid users.Coverage — what fraction of paid users ever fire the event?
  5. 05

    Step 3: Lock the falsifiable definition

    Write: "For \, activation = \ within \ after signup." The time-to-event window is the median time from signup to event among activated, retained users — not an aspiration. The window is part of the definition; events outside the window do not count.

    Write: "For \, activation = \ within \ after signup." The time-to-event window is the median time from signup to event among activated, retained users — not an aspiration. The window is part of the definition; events ou…

Permission review

Static risk signals and limitations

No configured static risk pattern was detected

This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score88/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars7SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
event4u-app/agent-config
Skill path
src/skills/activation-design/SKILL.md
Commit
0adf49a8ae84b0ff6e2de8759eea43257e020eff
License
MIT
Collected
2026-07-28
Default branch
main
View the original SKILL.md

activation-design

When to use

  • The activation event is "signed up" or "logged in" and the funnel looks healthy while retention sinks — the event does not correlate with paid or D30, so the metric is a vanity surface.
  • A new segment is being routed against an activation event built for a previous segment — the aha moment differs by segment and the metric needs to be re-keyed.
  • A product loop redesign needs activation to complete the loop's first cycle (handover from retention-loops) — the activation event must match the binding loop's first reward, not an arbitrary product step.

Do NOT use to design the day-0-to-day-30 milestone path (route to onboarding-design), the long-running retention loops themselves (route to retention-loops), or the full visitor-to-paid funnel diagnosis (route to funnel-analysis).

Cognition cluster

  • Mental model 9 — Hypothesis-driven thinking. "Event E is the activation moment because users who reach E retain at <rate> vs <base>" is a falsifiable claim with evidence. "E feels important" is not. Pick the event that survives the hypothesis test. See docs/contracts/mental-models.md § 9.
  • Mental model 16 — Leading vs. lagging indicators. Paid is lagging; the activation event must be leading — observable before the user has paid, and correlated with the lagging outcome. An activation event that is itself lagging cannot drive a decision in time. See mental-models.md § 16.
  • Mental model 13 — Occam's razor. When candidate events compete, the simpler one (single observable action) wins if it correlates as well as a composite. Composite events hide noise behind apparent precision. See mental-models.md § 13.
  • Context-spine — product + customer-segment + funnel-stage. Read the product slot for what counts as a meaningful buyer action in-product (the action must be observable in instrumentation), the customer-segment slot for the segment's switch-event (the aha moment is the segment's job done once), and the funnel-stage slot for activation's position relative to signup and paid. See context-spine.

Procedure

Step 0: Inspect — name the current activation event and its correlation

Inspect the existing definition. Verify by computing correlation between the event and paid conversion / D30 retention on the trailing four cohorts. If r < 0.4 with paid, the event is mis-defined; if r > 0.4 but the event is downstream of paid, it is lagging and useless for in-funnel decisions.

Step 1: Generate three candidate activation events

Each candidate is one observable user action that:

  1. Is in-product, in-instrumentation, in-segment-shape. No surveys, no proxies, no inferences from secondary signals.
  2. Sits upstream of paid in the funnel. Activation that requires paid is a retention metric, not an activation metric.
  3. Maps to the segment's switch-event. The candidate is the segment's "job done once" — not the vendor's vision of value.

Step 2: Compute correlation per candidate

For each candidate, compute on the trailing four cohorts:

  1. Correlation with paid conversion (point-biserial r).
  2. Correlation with D30 retention among paid users.
  3. Coverage — what fraction of paid users ever fire the event? A candidate with high r and low coverage is a niche aha, not the segment's aha.

The candidate that maximises (r-paid × r-retention × coverage) is the binding event. Verify it passes the simplicity check (Occam): if a composite event wins by < 10 % over a simpler single-action event, pick the simpler one.

Step 3: Lock the falsifiable definition

Write: "For <segment>, activation = <observable action> within <time-to-event window> after signup." The time-to-event window is the median time from signup to event among activated, retained users — not an aspiration. The window is part of the definition; events outside the window do not count.

Step 4: Hand back to onboarding and retention

The activation event is the target of onboarding milestones (route to onboarding-design for the milestone path that ends at this event) and the first cycle of the binding retention loop (route to retention-loops for the loop that begins from this event). Activation work without these two handoffs is metric theatre.

Step 5: Run the recheck every quarter

Each quarter, recompute the correlation on the latest four cohorts. Segment shape, pricing, or packaging shifts can move the aha moment by one step. Verify the binding event still maximises r × coverage; if a new candidate now wins, propose a redefinition, do not silently switch the event mid-quarter.

Related Skills

WHEN to use this

  • Defining or auditing the activation event for a segment.
  • Verifying correlation with paid / D30 against alternatives.

WHEN NOT to use this

  • Designing the days 0–30 milestone path itself — route to onboarding-design.
  • Designing the retention loops that begin at activation — route to retention-loops.
  • Full visitor → paid funnel diagnosis — route to funnel-analysis.

When the agent should load this

  • "What is our aha moment?"
  • "Redefine activation for the mid-market segment."
  • "Does our activation event actually correlate with paid?"
  • "Welches Event ist der echte Aha-Moment?"

Output

  1. activation-definition.md — segment · observable action · time-to-event window · trailing-cohort correlation with paid and D30 · coverage.
  2. candidates-shortlist.md — three candidate events scored by r-paid × r-retention × coverage; simplicity check noted.
  3. recheck-cadence.md — quarterly recheck plan: which cohorts feed the recompute · what would force a redefinition · who owns it.

Gotcha

  • An activation event that does not correlate with paid is a vanity event; the funnel looks fine while D30 keeps falling. Correlation comes before celebration.
  • "Composite" activation events that combine three actions hide noise behind apparent precision; the simpler single-action event usually carries the segment's switch-event better.
  • Switching the activation event mid-quarter without an A/B holdout destroys longitudinal comparison; propose a redefinition between quarters, with the recompute as evidence.

Do NOT

  • Do NOT pick activation by vendor narrative or pitch deck; the event must be observable in-product and falsifiable against retention.
  • Do NOT define activation as something that requires paid status; activation is the leading event, paid is the lagging event.
  • Do NOT use an industry-standard activation event ("first dashboard viewed", "first integration") without verifying segment correlation; segment shape dominates the choice.

Runnable example

B2B mid-market analytics tool, current activation = "user viewed dashboard", D30 retention 58 % despite activation rate 71 %.

  • Step 0 inspect — "viewed dashboard" correlation with D30 paid retention r = 0.18; activation is decoupled from outcome. Flagged for redefinition.
  • Step 1 candidates — (C1) connected one data source + rendered one dashboard (single action chain); (C2) saved one query; (C3) shared one dashboard with one teammate (network proxy).
  • Step 2 scores — C1: r-paid 0.54 · r-retention 0.61 · coverage 0.78. C2: r-paid 0.34. C3: r-paid 0.41 · coverage 0.22 (niche). Winner: C1. Simplicity check: passes (single action chain).
  • Step 3 definition — "Mid-market activation = first data source connected and first dashboard rendered, within 24 hours of signup."
  • Hand-off — onboarding milestone path retargeted at C1 (onboarding-design); retention loop L1 from retention-loops begins at C1's first cycle. Quarterly recheck owned by RevOps.

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