launchdarkly-flag-targeting

launchdarkly/agent-skills · updated Apr 8, 2026

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$npx skills add https://github.com/launchdarkly/agent-skills --skill launchdarkly-flag-targeting
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summary

You're using a skill that will guide you through changing who sees what for a feature flag. Your job is to understand the current state of the flag, figure out the right targeting approach for what the user wants, make the changes safely, and verify the resulting state.

skill.md

LaunchDarkly Flag Targeting & Rollout

You're using a skill that will guide you through changing who sees what for a feature flag. Your job is to understand the current state of the flag, figure out the right targeting approach for what the user wants, make the changes safely, and verify the resulting state.

Prerequisites

This skill requires the remotely hosted LaunchDarkly MCP server to be configured in your environment.

Required MCP tools:

  • get-flag — understand current state before making changes
  • toggle-flag — turn targeting on or off for a flag in an environment
  • update-rollout — change the default rule (fallthrough) variation or percentage rollout
  • update-targeting-rules — add, remove, or modify custom targeting rules
  • update-individual-targets — add or remove specific users/contexts from individual targeting

Optional MCP tools:

  • copy-flag-config — copy targeting configuration from one environment to another

Core Concept: Evaluation Order

Before making any targeting changes, understand how LaunchDarkly evaluates flags. This determines what your changes actually do:

  1. Flag is OFF → Serve the offVariation to everyone. Nothing else matters.
  2. Individual targets → If the context matches a specific target list, serve that variation. Highest priority.
  3. Custom rules → Evaluate rules top-to-bottom. First matching rule wins.
  4. Default rule (fallthrough) → If nothing else matched, serve this variation or rollout.

This means: if you add a targeting rule but the flag is OFF, nobody sees the change. If you set a percentage rollout on the default rule but there's an individual target, that targeted user bypasses the rollout.

Workflow

Step 1: Understand Current State

Before changing anything, check what's already configured.

  1. Confirm the environment. "Turn it on" without specifying an environment is ambiguous. Always confirm which environment the user means. Default to asking rather than assuming.
  2. Fetch the flag. Use get-flag with the target environment to see:
    • on — Is targeting currently enabled?
    • fallthrough — What's the default rule? (variation or percentage rollout)
    • offVariation — What serves when the flag is off?
    • rules — Any custom targeting rules?
    • targets — Any individually targeted users/contexts?
    • prerequisites — Any flags this depends on?
  3. Assess complexity. A flag with no rules and no individual targets is simple. A flag with multiple rules, targets, and prerequisites needs more care.

Step 2: Determine the Right Approach

Based on what the user wants and what you found, choose the right tool and strategy. See Targeting Patterns for the full reference.

Common scenarios:

User wants Tool Notes
"Turn it on" toggle-flag with on: true Simplest change
"Turn it off" toggle-flag with on: false Serves offVariation to everyone
"Roll out to X%" update-rollout with rolloutType: "percentage" Weights must sum to 100
"Enable for beta users" update-targeting-rules — add a rule with clause Rules are ANDed within, ORed between
"Add specific users" update-individual-targets Highest priority, overrides all rules
"Full rollout" update-rollout with rolloutType: "variation" Serve one variation to everyone
"Copy from staging" copy-flag-config Promote tested config to production

Step 3: Run the Safety Checklist

Before applying changes, especially in production, run through the Safety Checklist. The key checks:

  1. Right environment? Double-check you're targeting the intended environment.
  2. Approval required? Some environments require approval workflows. If toggle-flag or other tools return requiresApproval: true, surface this to the user with the approval URL.
  3. Prerequisite flags? If this flag has prerequisites, they must be met before targeting works as expected.
  4. Rule ordering impact? If adding rules, consider where they fall in evaluation order. Rules evaluate top-to-bottom, first match wins.
  5. Include a comment. Always add an audit trail comment, especially for production changes.

Step 4: Apply Changes

Use the appropriate tool for the change. Key notes:

  • toggle-flag: Specify on: true or on: false, the env, and a comment.
  • update-rollout: Use rolloutType: "percentage" with human-friendly weights (e.g., 80 for 80%) that sum to 100, or rolloutType: "variation" with a variationIndex.
  • update-targeting-rules: Instructions support addRule, removeRule, updateRuleVariationOrRollout, addClauses, removeClauses, reorderRules.
  • update-individual-targets: Instructions support addTargets, removeTargets, addContextTargets, removeContextTargets, replaceTargets.

See Targeting Patterns for detailed instruction examples.

Step 5: Verify

After applying changes, confirm the result:

  1. Fetch the updated flag. Use get-flag again to verify the new state.
  2. Confirm what the user expects. Describe the resulting targeting in plain language:
    • "The flag is now ON in production, serving true to 25% of users and false to 75%."
    • "Beta users now see variation A. Everyone else gets the default (variation B)."
  3. Check for side effects. If there are rules or individual targets, make sure the change interacts correctly with them.

Important Context

  • update-rollout uses human-friendly percentages. Pass 80 for 80%, not 80000. The tool handles the internal weight conversion.
  • Weights must sum to 100. For percentage rollouts, the weights across all variations must total exactly 100.
  • Rule ordering matters. Rules evaluate top-to-bottom. Reordering rules can change behavior without changing any individual rule.
  • Individual targets are highest priority. They override all rules and the default. Adding someone as an individual target means rules don't apply to them.
  • "Launched" flags are still ON. A flag with status "launched" is serving a single variation to everyone. If you want to remove the flag, use the cleanup skill, not targeting changes.

References

  • Targeting Patterns — Rollout strategies, rule construction, individual targeting, and cross-environment copying
  • Safety Checklist — Pre-change verification, approval workflows, environment awareness
how to use launchdarkly-flag-targeting

How to use launchdarkly-flag-targeting on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add launchdarkly-flag-targeting
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/launchdarkly/agent-skills --skill launchdarkly-flag-targeting

The skills CLI fetches launchdarkly-flag-targeting from GitHub repository launchdarkly/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/launchdarkly-flag-targeting

Reload or restart Cursor to activate launchdarkly-flag-targeting. Access the skill through slash commands (e.g., /launchdarkly-flag-targeting) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.658 reviews
  • Nikhil Iyer· Dec 24, 2024

    I recommend launchdarkly-flag-targeting for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Charlotte Iyer· Dec 24, 2024

    Useful defaults in launchdarkly-flag-targeting — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Charlotte Desai· Dec 20, 2024

    We added launchdarkly-flag-targeting from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chaitanya Patil· Dec 16, 2024

    Keeps context tight: launchdarkly-flag-targeting is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Jin Garcia· Dec 8, 2024

    launchdarkly-flag-targeting is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Nikhil Gupta· Nov 27, 2024

    Solid pick for teams standardizing on skills: launchdarkly-flag-targeting is focused, and the summary matches what you get after install.

  • Nikhil Perez· Nov 15, 2024

    launchdarkly-flag-targeting reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Henry Mensah· Nov 15, 2024

    Registry listing for launchdarkly-flag-targeting matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Piyush G· Nov 7, 2024

    launchdarkly-flag-targeting has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Oct 26, 2024

    Solid pick for teams standardizing on skills: launchdarkly-flag-targeting is focused, and the summary matches what you get after install.

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