The Best Feature Flag Cleanup Tools in 2026

The average enterprise application contains dozens to hundreds of feature flags. In our experience working with engineering teams, the vast majority of those flags are never properly removed. That translates to a growing backlog of dead flags per codebase -- each one adding conditional logic, increasing testing complexity, and slowing down every developer who has to navigate around them.

The industry has finally started treating this as a first-class problem. Where flag cleanup used to mean a quarterly "flag removal day" armed with grep and a prayer, 2026 offers a genuine ecosystem of tools ranging from purpose-built cleanup platforms to built-in features within flag management systems.

But the landscape is fragmented. Some tools focus on flag evaluation and targeting, others on code-level detection, and a few on the full lifecycle from creation to removal. Choosing the wrong category of tool means solving the wrong problem entirely.

This guide covers every meaningful option available in 2026, organized by approach, with honest assessments of what each tool does well and where it falls short. Whether you're a 5-person startup or a 500-person engineering organization, there's a tool here that fits your needs.

Understanding the tool categories

Before comparing individual tools, it helps to understand that "feature flag tools" fall into three distinct categories. Many teams make the mistake of conflating them.

Category 1: Flag management platforms

These are the tools most people think of when they hear "feature flag tool." They handle flag creation, targeting, evaluation, experimentation, and operational controls. Examples: LaunchDarkly, Split.io, DevCycle, Unleash, Statsig.

What they solve: Creating and managing flags in production -- who sees what, when, and under what conditions.

What they don't solve: Removing flag code from your codebase once the flag has served its purpose.

Category 2: Flag cleanup tools

These tools focus specifically on detecting stale flags in your source code and automating their removal. Examples: FlagShark, Piranha.

What they solve: Finding flags that should be removed, tracking their lifecycle, and generating the code changes needed to clean them up.

What they don't solve: Flag creation, targeting, or runtime evaluation.

Category 3: Hybrid approaches

Some flag management platforms include cleanup-adjacent features (like LaunchDarkly's Code References). Some cleanup tools include lightweight lifecycle management. And some teams build custom solutions that bridge both categories.

The key insight: Most teams need tools from both Category 1 and Category 2. A flag management platform tells you that a flag exists and who it targets. A cleanup tool tells you where in your code that flag lives, whether it's stale, and automates the PR to remove it.

The master comparison

Here's how every significant tool in the space stacks up across the dimensions that matter most for flag cleanup:

Tool	Category	Cleanup Focus	Code Detection	Auto-Removal PRs	Languages	Pricing
FlagShark	Cleanup	Primary	Tree-sitter (11 langs)	Yes	11	Subscription
Piranha	Cleanup	Primary	Tree-sitter + rules	No (generates diffs)	8	Free (OSS)
LaunchDarkly	Management + Code Refs	Secondary	Regex (Code Refs)	No	20+ (Code Refs)	$$$$
Split.io	Management	Minimal	Limited	No	N/A	$$$
DevCycle	Management	Secondary	Built-in tracking	No	10+	$$
Unleash	Management	Secondary	Staleness markers	No	N/A	$ - $$
Statsig	Management	Minimal	Limited	No	N/A	$$
Custom (ESLint/grep)	DIY	Variable	Regex/AST	Manual	Per-implementation	Free (+ eng time)

Now let's examine each tool in detail.

1. FlagShark

What it is: A purpose-built SaaS platform for automated feature flag cleanup that integrates as a GitHub App.

How it works: FlagShark monitors your GitHub repositories continuously. When a developer opens a pull request that adds or modifies feature flags, FlagShark detects the changes using tree-sitter AST parsing, comments on the PR with flag information, and begins lifecycle tracking. When flags become stale based on configurable criteria, FlagShark automatically generates cleanup pull requests that remove the dead flag code.

The detection engine supports 11 programming languages with built-in knowledge of major flag providers (LaunchDarkly, Unleash, Split, and custom SDKs configurable via .flagshark.yaml). Because it tracks the full lifecycle -- from the PR where a flag was introduced to the PR that removes it -- FlagShark can make intelligent decisions about which flags are actually stale versus which are still actively being rolled out.

Key strengths:

• Zero configuration: Install the GitHub App and it works immediately. No rule files, no CI pipeline changes, no infrastructure to maintain.
• Continuous monitoring: Every PR is analyzed in real time, not just during scheduled cleanup runs. This prevents flag debt from accumulating silently.
• Lifecycle tracking: Full history of every flag -- when it was introduced, which PRs reference it, when it was last modified, and when it qualifies as stale.
• Automated cleanup PRs: Generates production-ready pull requests that remove stale flag code, ready for team review and merge.
• Multi-provider support: Works with any flag SDK, not just a single vendor's ecosystem.

Limitations:

• GitHub-only (no GitLab or Bitbucket support currently)
• SaaS model means your code is analyzed by an external service
• Subscription pricing may not fit every budget

Best for: Teams using GitHub that want automated, continuous flag cleanup without investing engineering time in setup or maintenance. Particularly strong for small-to-mid-size teams (5-100 engineers) using standard flag SDKs.

Pricing: Subscription-based, tiered by repository count and team size.

2. Piranha (Uber)

What it is: An open-source automated refactoring tool created by Uber Engineering, designed to detect and remove stale feature flags from source code.

How it works: Piranha uses tree-sitter to parse your codebase and applies user-defined rules to identify and transform stale flag code. You provide Piranha with a list of flags to remove and their resolved values (e.g., "flag X should resolve to true"), and Piranha generates the code transformations needed to remove the conditional logic and dead code branches.

The original Piranha supported Java, Swift, and Objective-C. The current version, Polyglot Piranha, was rewritten in Rust and supports a broader set of languages through a unified rule engine.

Key strengths:

• Free and open-source: No licensing costs, full source code access, community-driven development
• Proven at scale: Successfully removed approximately 2,000 stale flags from Uber's mobile applications
• Maximum flexibility: Raw tree-sitter query access means you can match virtually any code pattern
• Academic rigor: Backed by published research (IEEE/ACM), well-documented approach
• No external service: Your code never leaves your infrastructure

Limitations:

• Significant setup investment: Writing tree-sitter rules for your specific flag patterns requires expertise and time (hours to days)
• No stale flag detection: Piranha doesn't determine which flags are stale -- you must provide that list from another source
• No continuous monitoring: Batch tool that runs on-demand or on a schedule, not integrated into the PR workflow
• Maintenance burden: Rules must be updated as your flag SDKs and code patterns evolve
• No automatic PR generation: Produces diffs that you must manually turn into pull requests

Best for: Large engineering organizations with dedicated platform teams, especially those with custom flag SDKs or highly non-standard patterns. Teams that prioritize full control and have the engineering bandwidth to invest in tooling.

Pricing: Free (open-source). True cost includes engineering time for setup, rule maintenance, and infrastructure.

3. LaunchDarkly Code References

What it is: A feature within LaunchDarkly's flag management platform that scans your source code to identify where flags are referenced.

How it works: LaunchDarkly's Code References feature uses a CLI tool (ld-find-code-refs) that you integrate into your CI/CD pipeline. On each build, it scans your codebase for LaunchDarkly flag keys and reports the file locations, line numbers, and surrounding context back to the LaunchDarkly dashboard. When a flag's code references drop to zero, LaunchDarkly marks it as a candidate for archival.

Key strengths:

• Tight integration with LaunchDarkly: If you're already using LaunchDarkly, Code References provides a unified view of flags across both the management platform and your codebase
• Broad language support: The regex-based scanner works with 20+ languages out of the box
• Flag status correlation: Combines code presence with flag evaluation data, targeting rules, and operational status
• Extinction detection: Automatically identifies flags with zero code references

Limitations:

• LaunchDarkly-only: Only detects flags managed through LaunchDarkly's SDK. Custom flags, other providers' SDKs, and ad-hoc flag implementations are invisible.
• No code removal: Identifies where flags exist but doesn't generate removal code or cleanup PRs. The "last mile" of actually removing flag code remains manual.
• Regex-based detection: Uses pattern matching rather than AST parsing, which means higher false positive rates for flag keys that appear in comments, strings, or variable names.
• Requires LaunchDarkly subscription: This is a feature within LaunchDarkly's paid platform, not a standalone tool.
• One-directional: Shows code references in the LaunchDarkly dashboard but doesn't comment on PRs or integrate into the developer's code review workflow.

Best for: Teams already heavily invested in the LaunchDarkly ecosystem who want better visibility into flag usage across their codebase. Most valuable as a complement to, not replacement for, a dedicated cleanup tool.

Pricing: Included in LaunchDarkly Pro and Enterprise plans. Check LaunchDarkly's website for current pricing as it changes frequently.

4. Split.io

What it is: A feature delivery and experimentation platform with some flag lifecycle management capabilities.

How it works: Split provides feature flag management, experimentation, and targeting capabilities. For cleanup, Split offers flag status tracking -- you can see which flags are active, which are killed (permanently off), and which have been at 100% rollout for extended periods. Split also integrates with monitoring tools to track flag evaluation frequency.

Key strengths:

• Strong experimentation focus: If your flags are primarily for A/B testing and experimentation, Split's statistical engine is industry-leading
• Flag health indicators: Dashboard shows flag age, last modification, evaluation frequency, and status
• Data-driven decisions: Combines flag management with product analytics to determine when experiments should conclude
• SDK breadth: Supports most major languages and frameworks

Limitations:

• No code-level detection: Split tracks flags within its own system but doesn't scan your source code. It knows a flag exists but not where in your codebase it's referenced.
• No cleanup automation: No automated code removal, no PR generation, no refactoring capabilities
• Split-only flags: Only manages flags created through Split's platform. Any flags using other providers or custom implementations are outside its scope.
• Cleanup is still manual: Identifying stale flags is possible through the dashboard, but the actual code cleanup remains a manual engineering task

Best for: Teams focused on experimentation and product analytics who need better visibility into flag health within their flag management platform. Not a replacement for code-level cleanup tools.

Pricing: Custom pricing, typically $$ to $$$ range depending on volume and features.

5. DevCycle

What it is: A feature flag management platform that positions itself as developer-focused, with built-in code tracking and cleanup-oriented features.

How it works: DevCycle provides flag management, targeting, and experimentation with a stronger emphasis on the developer workflow than most competitors. Their "Code Usages" feature tracks where flags are referenced in your codebase through SDK integration. DevCycle also provides flag lifecycle stages (development, staging, production, cleanup) and can mark flags as "ready for cleanup" based on configurable criteria.

Key strengths:

• Developer-centric design: CLI tools, local development support, and code-first workflows
• Code Usages tracking: Shows where flags are used in your codebase through SDK telemetry
• Lifecycle stages: Built-in concept of flag lifecycle from development through cleanup
• Competitive pricing: Generally more affordable than LaunchDarkly for equivalent features
• OpenFeature compliance: Strong commitment to the OpenFeature standard

Limitations:

• No automated code removal: Code Usages shows where flags are referenced, but cleanup is still manual
• SDK-dependent detection: Only tracks flags evaluated through DevCycle's SDK, not other implementations
• Newer platform: Smaller community and ecosystem compared to LaunchDarkly or Unleash
• No cross-provider support: Only manages flags within the DevCycle ecosystem

Best for: Teams evaluating flag management platforms who want built-in lifecycle awareness and a developer-friendly experience. A good choice for the management side, but still needs a separate cleanup tool for automated code removal.

Pricing: Free tier available, paid plans from $12/seat/month.

6. Unleash

What it is: An open-source feature flag management platform with self-hosted and cloud options.

How it works: Unleash provides feature flag creation, targeting, and evaluation with a strong open-source community. For cleanup, Unleash offers "potentially stale" markers -- flags that have been active longer than their configured lifetime are automatically flagged in the dashboard. Unleash also supports flag types (release, experiment, operational, kill-switch) with recommended lifetimes for each.

Key strengths:

• Open-source core: Self-host for free, full source code access, active community
• Staleness detection: Built-in concept of flag lifetimes and automatic staleness markers
• Flag types with guidelines: Predefined flag categories with recommended expiration periods
• Self-hosted option: For teams that need flags to stay within their infrastructure
• OpenFeature support: Compatible with the OpenFeature standard

Limitations:

• No code-level detection: Unleash tracks flags within its own system but doesn't know where flags are referenced in your source code
• No cleanup automation: Staleness markers are informational only -- no automated code removal or PR generation
• Dashboard-only alerts: Stale flag notifications appear in the Unleash dashboard, not in your development workflow (PRs, IDE, CI)
• Manual cleanup process: Engineers must manually find and remove stale flag code

Best for: Teams wanting an open-source or self-hosted flag management platform with basic lifecycle awareness. The staleness features are helpful for the management side but don't address code-level cleanup.

Pricing: Free (open-source self-hosted), Pro from $80/month, Enterprise custom pricing.

7. Statsig

What it is: A feature management and experimentation platform with strong product analytics integration.

How it works: Statsig combines feature flags with product analytics and experimentation. For lifecycle management, Statsig provides flag evaluation metrics and can identify flags that haven't been evaluated recently or that have been at 100% rollout for extended periods. Their "Diagnostics" features help identify flags that may be ready for cleanup.

Key strengths:

• Analytics-first approach: Deep integration between flags, experiments, and product metrics
• Evaluation diagnostics: Identifies flags with declining or zero evaluation rates
• Cost-effective: Generous free tier for smaller teams
• Experimentation depth: Strong statistical engine for A/B testing

Limitations:

• Minimal cleanup tooling: Flag diagnostics can identify candidates, but there's no code-level detection or automated removal
• Platform-specific: Only tracks flags managed through Statsig's SDK
• No code scanning: Doesn't know where flags are referenced in your source code
• Manual cleanup required: All code removal is manual

Best for: Teams focused on experimentation and product analytics. Statsig excels as a flag management and experimentation platform but doesn't meaningfully address the code cleanup problem.

Pricing: Free tier (up to 1M events), Pro plans with custom pricing.

8. Custom solutions: ESLint rules, grep scripts, and CI checks

What it is: Homegrown tooling built by engineering teams to address flag cleanup in the absence of (or as a complement to) commercial tools.

How it works: The most common custom approaches include:

ESLint / linter rules: Custom rules that flag deprecated feature flags in code:

// .eslintrc custom rule
"no-restricted-properties": ["error", {
  "object": "flags",
  "property": "OLD_CHECKOUT_FLOW",
  "message": "This flag has been deprecated. Remove this code path."
}]

Grep / ripgrep scripts: Scheduled scripts that scan for known flag keys:

#!/bin/bash
# Find all references to deprecated flags
STALE_FLAGS=("OLD_CHECKOUT_v2" "TEMP_AUTH_BYPASS" "EXPERIMENT_47")
for flag in "${STALE_FLAGS[@]}"; do
  echo "=== $flag ==="
  rg "$flag" --type-add 'src:*.{ts,js,go,py}' -t src -c
done

CI pipeline checks: Build-time validation that fails if stale flags are detected:

# GitHub Actions step
- name: Check for stale flags
  run: |
    if grep -r "DEPRECATED_FLAG_NAME" src/; then
      echo "Stale flag detected. Please remove before merging."
      exit 1
    fi

Git hooks: Pre-commit hooks that warn about known stale flags.

Key strengths:

• Free: No software costs beyond engineering time
• Customizable: Tailored exactly to your codebase and workflow
• Educational: Building cleanup tooling teaches the team about flag patterns
• No vendor dependency: Fully within your control

Limitations:

• Regex-based detection: Most custom solutions use pattern matching, which is fundamentally less accurate than AST parsing. False positives from comments, strings, and variable names are common.
• Significant maintenance burden: Rules must be updated manually for every new stale flag, every new flag pattern, and every new language
• No lifecycle tracking: These tools are point-in-time checks, not lifecycle management systems
• Doesn't scale: Works for 10-20 flags, becomes unmanageable at 100+
• Knowledge concentration: The engineer who built the tooling becomes a single point of failure
• No automatic removal: Detection only -- the actual code cleanup is still manual

Best for: Teams with fewer than 20 flags who want basic guardrails without adopting a new tool. Also useful as a stopgap while evaluating dedicated cleanup solutions.

Pricing: Free (+ ongoing engineering time, typically 4-8 hours/month for maintenance).

Choosing the right tool: A decision framework

With eight options on the table, the decision can feel overwhelming. Here's a framework to narrow it down based on your team's specific situation.

Step 1: Determine what you already have

If you're already using a flag management platform (LaunchDarkly, Split, Unleash, etc.), you have the "creation and targeting" side covered. What you likely need is a complementary cleanup tool that handles the code-level detection and removal that your management platform doesn't do.

If you're not using a flag management platform and are evaluating the full stack, DevCycle and Unleash offer the best built-in lifecycle awareness among the management platforms, but you'll still benefit from a dedicated cleanup tool alongside them.

Step 2: Assess your cleanup needs

Situation	Recommended Approach
< 20 flags, small team	Custom ESLint rules or grep scripts may suffice
20-100 flags, standard SDKs	Dedicated cleanup tool (FlagShark or Piranha)
100+ flags, multiple languages	Dedicated cleanup tool is essential
Custom internal SDKs	Piranha's rule flexibility or FlagShark with .flagshark.yaml
Batch cleanup of known stale flags	Piranha for the initial sweep
Continuous prevention of flag debt	FlagShark for ongoing monitoring

Step 3: Evaluate your constraints

Budget vs. engineering time tradeoff: Open-source tools (Piranha, Unleash, custom scripts) cost nothing in licensing but require meaningful engineering investment. SaaS tools (FlagShark, LaunchDarkly) trade subscription costs for time savings. For most teams, the engineering time saved by a managed solution far exceeds the subscription cost.

Infrastructure preferences: If your organization requires all code analysis to happen within your infrastructure, Piranha and custom solutions are your options. If SaaS tools are acceptable, FlagShark offers the fastest path to value.

GitHub vs. other platforms: FlagShark's GitHub App integration is a strength if you're on GitHub and a limitation if you're not. Piranha and custom solutions are platform-agnostic.

Step 4: Consider the stack approach

The most effective teams typically use a layered approach:

Layer	Tool	Purpose
Flag management	LaunchDarkly, Split, Unleash, DevCycle, or Statsig	Creation, targeting, evaluation, experimentation
Code cleanup	FlagShark, Piranha, or custom	Detection, lifecycle tracking, automated removal
Guardrails	ESLint rules, CI checks	Prevent introduction of known-stale flags

This layered approach ensures that flags are well-managed throughout their entire lifecycle, from creation to removal, without any gaps.

What the landscape looks like in 2026

The feature flag ecosystem has matured significantly. Flag management platforms are now table stakes for any serious engineering organization, and the cleanup problem is finally getting the attention it deserves.

The most notable trends:

AST-based detection is becoming the standard. Regex-based flag scanning is being replaced by tree-sitter and other AST parsing approaches that understand code structure, not just text patterns. This reduces false positives and enables more sophisticated transformations like dead branch elimination.

Lifecycle tracking is the differentiator. Knowing that a flag exists in your code is useful. Knowing when it was introduced, which PRs reference it, when it was last evaluated, and whether it's been at 100% rollout for 90 days -- that's what enables automated cleanup decisions.

The management-cleanup gap is closing. Flag management platforms are adding more lifecycle features, and cleanup tools are adding more management-adjacent capabilities. But the gap still exists -- no single tool does both exceptionally well in 2026. The layered approach remains the most effective strategy.

Open-source and SaaS coexist. Piranha has proven that open-source cleanup tools can work at massive scale. Tools like FlagShark have proven that SaaS can deliver the same outcomes with dramatically less setup effort. Teams are choosing based on their specific constraints rather than ideology.

The cost of doing nothing

Before closing, it's worth restating what's at stake. Based on what we've seen working with engineering teams:

• Developer time lost: Engineers regularly spend hours each week navigating dead flag code, reviewing unnecessary branches, and debugging issues caused by stale conditionals
• Code review friction: PRs that touch flagged code take longer to review because reviewers must mentally trace both active and dead paths
• Onboarding drag: New hires take longer to become productive when the codebase is cluttered with flags whose purpose and status are unclear
• Incident risk: Stale flags create latent failure modes -- the Knight Capital incident, where a forgotten code path caused a $460 million loss in 45 minutes, remains the most dramatic example

The tools exist. The ecosystem is mature. The question isn't whether automated flag cleanup is worth it -- the economics are overwhelming. The question is which tool fits your team's specific needs, constraints, and workflow.

---

Feature flag cleanup has evolved from a manual chore to a tooling-rich discipline. Whether you choose a dedicated cleanup platform, an open-source refactoring engine, built-in features from your flag management provider, or a custom approach, the critical step is choosing something and implementing it. The cost of stale flags compounds daily, and the tools available in 2026 make "we haven't gotten around to it" an increasingly indefensible position. Audit your flags, pick a tool, and start cleaning.