Feature Flags Architect

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

作者 alirezarezvani19392f7a0826MIT27K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫5 週前更新

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 產生的概覽

指導功能旗標全生命週期:分類旗標、規劃發布、稽核終止開關並掃描旗標債務。

功能
此技能提供功能旗標的端到端規範,涵蓋將旗標分類為發布、實驗、營運與權限四種類型,以及發布規劃、終止開關設計與退役清理。它附帶三個僅使用標準函式庫的 Python 指令碼:旗標債務掃描器、發布規劃器與終止開關稽核器。此外還包含四份參考文件(分類、供應商取捨、發布策略、生命週期)、一個旗標申請範本與一個清理斜線指令。
適用情境
適用於新增、退役或稽核功能旗標,設計漸進式發布或終止開關,在多個旗標供應商之間做選擇,或在發布凍結前清理過時旗標。
執行需求
執行三個附帶指令碼需要 Python 3 執行環境(僅標準函式庫);債務掃描器與終止開關稽核器需要 git 儲存庫;終止開關稽核需要一份旗標文件檔案。無需憑證或網路存取。

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

來源與署名

來源:alirezarezvani/claude-skills位於engineering/skills/feature-flags-architect提交19392f7

授權條款: MIT

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