Agents / Skills

Feature Flag Rollout

Skill

Plans a feature's release behind a flag properly: staged exposure, the metrics that gate each stage, kill-switch behaviour verified — and the flag's own funeral scheduled so it does not haunt the codebase forever.

Best for

  • Releases too risky for all-at-once
  • Teams whose codebase is an archaeology of dead flags
  • Making 'we can always turn it off' actually true

What you give it

  • The feature, its risk profile, and the metrics that would show trouble

What you get back

  • A staged rollout plan: cohorts, percentages, dwell times, and the gate metrics per stage
  • Kill-switch semantics defined and tested: what off means for in-flight users and their data
  • The removal plan: when the flag dies, who removes it, what reminds them

How it works

  1. Sizes the staging to the risk: money paths get shadow comparison; cosmetic changes get two stages, not five.
  2. Defines gates as metrics with thresholds, not vibes — each stage needs its evidence before widening.
  3. Specifies kill-switch semantics precisely: what off means for users mid-flow and data already written.
  4. Schedules the flag's removal at plan time, because flags planned without funerals become permanent residents.

Example

You: We are rolling out the new pricing calculation. If it is wrong, we lose money or trust. Plan it.

Result: Five stages: internal accounts, 1% of traffic with old-vs-new shadow comparison (mismatches logged, zero required to proceed), 10% with the error-rate and support-ticket gates, 50%, 100%. Kill-switch tested: off reverts to old calculation, in-flight checkouts complete on whichever version priced their cart. Flag removal scheduled two weeks after 100%, with the cleanup ticket pre-created.

Limits — please read

  • It plans within your flag tooling; introducing a flag system is a separate decision.
  • Shadow comparisons need the old and new paths to coexist — where they cannot, it says so and adjusts the design.
  • Gate metrics need instrumentation that exists; missing metrics are named as prerequisites.