Feature Flags Architect

alirezarezvani/claude-skills/engineering/skills/feature-flags-architect

作者 alirezarezvani19392f7a0826MIT27K 个星标收录于 2026年10月8日更新于 2026年10月8日仓库5周前更新

Use when adding, retiring, or auditing feature flags. Triggers on "add a flag", "ship behind a flag", "rollout plan", "kill switch", "stale flags", "flag debt", "LaunchDarkly", "GrowthBook", "Statsig", "Unleash", "Flipt", or any progressive-delivery question. Ships flag debt scanner, rollout planner, and kill-switch auditor (all stdlib Python), 4 references on flag taxonomy + provider trade-offs + rollout strategies + lifecycle, plus a /flag-cleanup slash command.

AI 生成的概览

指导功能开关全生命周期:分类开关、规划发布、审计终止开关并扫描开关债务。

功能
该技能提供功能开关的端到端规范,涵盖将开关分类为发布、实验、运维和权限四种类型,以及发布规划、终止开关设计和退役清理。它附带三个仅使用标准库的 Python 脚本:开关债务扫描器、发布规划器和终止开关审计器。此外还包含四份参考文档(分类、服务商权衡、发布策略、生命周期)、一个开关申请模板和一个清理斜杠命令。
适用场景
适用于新增、退役或审计功能开关,设计渐进式发布或终止开关,在多个开关服务商之间做选择,或在发布冻结前清理陈旧开关。
运行要求
运行三个附带脚本需要 Python 3 运行时(仅标准库);债务扫描器和终止开关审计器需要 git 仓库;终止开关审计需要一份开关文档文件。无需凭据或网络访问。

Feature Flags Architect

End-to-end discipline for feature flags: classify them, ship them, ramp them, and retire them. Most teams treat flags as throwaway if-statements; this skill treats them as a controlled lifecycle with measurable debt.

When to use

  • Adding a new flag and need a rollout plan
  • Auditing a codebase for stale or orphaned flags
  • Choosing a flag provider (LaunchDarkly vs GrowthBook vs Statsig vs Unleash vs Flipt vs build-your-own)
  • Designing a kill-switch path for a risky launch
  • Cleaning up flag debt before a release freeze
  • Reviewing whether a feature should ship behind a flag at all

Core principle: flags are a lifecycle, not an if

request → design → ship → ramp → cleanup → archive

Flags that skip cleanup become debt: dead branches, stale defaults, untested code paths, unbounded blast radius. The three scripts in this skill enforce the lifecycle.

Quick start

bash
# 1. Audit the repo for flag debtpython scripts/flag_debt_scanner.py --repo . --max-age-days 90
# 2. Plan a progressive rollout for a new flagpython scripts/rollout_planner.py --population 100000 --target-percent 100 --duration-days 14 --strategy ring
# 3. Verify every flag has a documented kill switchpython scripts/kill_switch_audit.py --repo . --flag-doc docs/feature-flags.md

The 4 flag types (taxonomy)

Different flag types have different lifespans and ownership. Misclassifying creates debt.

TypePurposeTypical lifespanOwnerCleanup trigger
ReleaseHide unfinished features in productiondays–weeksEng100% rollout reached
ExperimentA/B test variantsweeksProduct/MarketingTest concluded; winner picked
OperationalCircuit breakers, perf toggles, kill switchesmonths–yearsEng/SREReplaced by autoscaling/feature retirement
PermissionEntitlements per user/account/planyears (permanent)ProductPlan/role removed

Only Release and Experiment flags should be on a debt-scanner watchlist. Operational and Permission flags are by design long-lived. See references/flag_taxonomy.md for decision tree.

The 3 Python tools

All three are stdlib-only. Run with --help.

flag_debt_scanner.py

Finds flags older than --max-age-days with low usage, suggesting candidates for cleanup.

bash
python scripts/flag_debt_scanner.py --repo . --max-age-days 90 --format textpython scripts/flag_debt_scanner.py --repo . --max-age-days 60 --format json > debt.json

Detection heuristic:

  1. Walk --repo for code references matching common flag-call patterns:
    • flag("..."), isFlagEnabled("..."), featureFlag("..."), getFlag("...")
    • client.variation("...", ...), unleash.isEnabled("..."), growthbook.feature("...")
  2. For each unique flag identifier, find the oldest commit that introduced it (git log --diff-filter=A -S <name>).
  3. Flag as DEBT if introduced > --max-age-days ago AND used in ≤--min-uses places.

Outputs flag name, age in days, file references, suggested action. JSON mode is CI-friendly.

rollout_planner.py

Generates a phased rollout schedule from population size, target percent, duration, and strategy.

bash
python scripts/rollout_planner.py --population 100000 --target-percent 100 --duration-days 14 --strategy ringpython scripts/rollout_planner.py --population 50000 --target-percent 25 --duration-days 7 --strategy linearpython scripts/rollout_planner.py --population 1000000 --target-percent 100 --duration-days 30 --strategy log

Strategies:

  • ring: 1% → 5% → 25% → 50% → 100%, evenly spaced. Default for risky launches.
  • linear: constant rate per day. Default for medium-risk.
  • log: rapid early, slow tail. Default for low-risk launches with confidence.
  • cohort: by named cohort (internal → beta → free → paid → all).

Outputs a markdown table with date, percent, expected user count, abort criteria, and verification step per phase.

kill_switch_audit.py

Cross-references code-discovered flags against documentation to verify each has a kill switch path written down.

bash
python scripts/kill_switch_audit.py --repo . --flag-doc docs/feature-flags.mdpython scripts/kill_switch_audit.py --repo . --flag-doc runbooks/flags.md --format json

What it checks:

  1. Every code-discovered flag has an entry in --flag-doc
  2. Each entry declares: owner, type, kill-switch trigger, monitoring dashboard
  3. Reports flags missing documentation (FAIL) or missing fields (WARN)

Use as a pre-merge gate before any new flag ships.

Provider chooser (5 + DIY)

ProviderBest forPricing modelLock-in riskOSS option
LaunchDarklyEnterprise, complex targeting, audit/compliancePer-MAU, expensiveHighNo
GrowthBookMid-market, A/B testing focused, OSS-friendlyPer-MAU + OSSLowYes (self-host)
StatsigGrowth/product teams, advanced experimentationFree tier + per-MAUMediumNo
UnleashOSS-first, self-hosted, dev-friendlyOSS + EnterpriseLowYes
FliptLightweight, k8s-native, simple needsOSS-onlyNoneYes
DIY<100 flags, no targeting, full controlNoneNoneN/A

Decision rules:

  • <50 flags + no targeting → DIY with config file or env vars
  • Need analytics + experimentation → Statsig or GrowthBook
  • Compliance/SOC2 audit logs required → LaunchDarkly
  • Self-hosting required (data residency / air-gapped) → Unleash or Flipt
  • See references/provider_comparison.md for detail.

Workflows

Workflow 1: Ship a new feature behind a flag

1. Classify: which of the 4 flag types?   → Release (most common for engineering work)2. Run rollout_planner.py to design the ramp3. Add flag entry to docs/feature-flags.md BEFORE writing code:   - name, owner, type, kill-switch trigger, dashboard URL4. Write the code with the flag5. Run kill_switch_audit.py — must pass before merge6. Deploy at 0%; verify kill switch works7. Execute rollout schedule; abort if abort criteria met8. At 100% for 7+ days: remove flag, delete dead branch, archive doc entry

Workflow 2: Quarterly flag cleanup

1. Run flag_debt_scanner.py --repo . --max-age-days 90 > debt.md2. For each flagged item:   a. Confirm it reached 100% (or was killed)   b. Find the issue/PR that introduced it; verify owner agrees to remove   c. Delete dead branches; remove flag config   d. Run kill_switch_audit.py — should now show one fewer flag3. Update CHANGELOG: "Removed N stale flags"

Workflow 3: Choose a provider

1. Estimate flag count (current + 12-month projection)2. Required features:   - Targeting rules (user, account, geo, %)?   - A/B testing + stats?   - Audit log / SOC2?   - Self-hosting / data residency?3. Pricing budget (MAU * cost-per-MAU)4. See provider_comparison.md decision tree5. Build a 30-day proof-of-concept before signing

Workflow 4: Design a kill switch

1. Identify the failure modes:   - Latency spike (which threshold?)   - Error rate spike (which threshold?)   - Business metric regression (which threshold?)2. Wire each to an abort:   - Manual: dashboard link + on-call playbook   - Automated: alert threshold flips flag back to 0%3. Test the kill switch in staging BEFORE production rollout4. Document in flag-doc; pass kill_switch_audit.py

References

  • references/flag_taxonomy.md — 4 types, decision tree, ownership, lifespan
  • references/provider_comparison.md — LaunchDarkly / GrowthBook / Statsig / Unleash / Flipt / DIY trade-offs
  • references/rollout_strategies.md — ring / linear / log / cohort / geo, abort criteria, monitoring
  • references/flag_lifecycle.md — request → design → ship → ramp → cleanup → archive

Slash command

/flag-cleanup — Run the full cleanup workflow on the current repo: scan for debt, generate a removal plan, audit kill switches.

Asset templates

  • assets/flag_request_template.md — fill-in form for new flag requests (name, owner, type, kill switch, rollout plan)

Anti-patterns

  • Permanent flag with if (FLAG_FOO) 50 places — should be a Permission flag with a runtime config, not a Release flag
  • Flag with no owner — when the original engineer leaves, no one cleans it up
  • No kill switch documented — when the feature breaks, no one knows how to disable it
  • A/B test that ran 6 months — pick a winner; running indefinitely is debt
  • Flags as feature toggles for cosmetic changes — ship via deploy, not flag

Verifiable success

A team using this skill should achieve:

  • 100% of new flags pass kill_switch_audit.py at merge time
  • flag_debt_scanner.py --max-age-days 90 returns ≤5 stale flags repo-wide
  • Every flag has a documented owner, type, and kill switch
  • Mean time to retire a Release flag: <60 days from 100% rollout

来源与署名

来源:alirezarezvani/claude-skills位于engineering/skills/feature-flags-architect提交19392f7

许可证: MIT

内容归原作者所有。SourceWeft 从公开仓库中收录这些内容。

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