Vard Traction

VARD Traction

Invoke as $vard-traction.

Post-launch traction check for shipped VARD experiments. Reads the ship log and current signals, compares them against the VARD graduation thresholds, and recommends exactly one of: iterate, graduate to Business AFPS, or archive. This is the semi-automatic graduation gate — the skill recommends, you confirm before anything happens.

Process

1. Resolve target: Use $ARGUMENTS to name the shipped concept. If omitted, use the most recent launched entry in research/vard-ship-log.md.
2. Confirm timing: Traction is meaningful after 1-2 weeks live. If the ship date is more recent, note the signal is early and mark the recommendation provisional.
3. Gather signals: Collect the available distribution and engagement signals for the app:
   • Users / unique visitors
   • Shares and social engagement (is the viral mechanic working?)
   • Core-action completion (the one thing the app does)
   • Revenue or revenue-intent signals
   • Inbound interest (enterprise inquiries, feature requests, press) Use the analytics wired at ship time. Where a signal is unavailable, mark it unknown rather than guessing.
4. Compare to graduation thresholds: Evaluate against the VARD graduation triggers:
   • Enterprise inquiry or clear revenue potential → strong graduate signal (Business AFPS)
   • User base large enough to justify deep customer discovery → graduate signal
   • Sustained engagement or sharing growth → iterate-and-grow signal
   • Flat or no traction after 1-2 weeks → archive signal
5. Recommend (semi-auto gate): Produce exactly one recommendation with its rationale and the signals that drove it:
   • Graduate → install the Business AFPS entry pack with npx skillpacks install business-research, then enter at $idea-scope-brief for raw/new product framing or $customer-discovery when the shipped app already has a clear concept and traction evidence. Link the VARD scan, align, ship-log, and traction-log entries as evidence.
   • Iterate → keep it in VARD; run another build and distribution cycle.
   • Archive → record the outcome and move on to the next experiment. State explicitly that the user confirms before any graduation, archive, or further action happens.
6. Log the check: Append a traction entry under the concept in research/vard-ship-log.md:
   • Date of check, weeks since launch
   • Each signal and its value (or unknown)
   • Threshold comparison result
   • Recommendation and rationale
   • Status: iterating, graduating, or archived

Output

End with:

**Traction:** <concept name> — <one-line signal summary>
**Recommendation:** iterate | graduate to Business AFPS | archive
**Next work:** <the confirming action for the recommendation>
**Recommended next command:** npx skillpacks install business-research, then $idea-scope-brief or $customer-discovery (graduate) | $vard-scan (next experiment) | none (archived)

Constraints

• Do not run paid API calls or external account actions to gather signals.
• Do not graduate, archive, or delete anything automatically — recommend and let the user confirm.
• Mark unavailable signals as unknown; do not fabricate metrics.
• If no ship-log entry exists for the target, report that and stop.
• Create research/vard-ship-log.md with a header only if it is missing and a shipped app clearly exists.

Cross-Pack Routing

A graduation to Business AFPS requires the business-research pack. If it is not installed, include npx skillpacks install business-research as the prerequisite. Use $idea-scope-brief when the opportunity still needs raw or new product framing; use $customer-discovery when the shipped app has a clear concept and traction evidence ready for deliberate customer research.

Default Shipping Contract

Follow the shared shipping contract convention.