You're using a skill that will guide you through auditing and understanding the feature flag landscape in a LaunchDarkly project. Your job is to explore the project, assess the health of its flags, identify what needs attention, and provide actionable recommendations.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionlaunchdarkly-flag-discoveryExecute the skills CLI command in your project's root directory to begin installation:
Fetches launchdarkly-flag-discovery from launchdarkly/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate launchdarkly-flag-discovery. Access via /launchdarkly-flag-discovery in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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You're using a skill that will guide you through auditing and understanding the feature flag landscape in a LaunchDarkly project. Your job is to explore the project, assess the health of its flags, identify what needs attention, and provide actionable recommendations.
This skill requires the remotely hosted LaunchDarkly MCP server to be configured in your environment.
Required MCP tools:
list-flags — search and browse flags with filtering by state, type, tagsget-flag — get full configuration for a single flag in a specific environmentget-flag-status-across-envs — check a flag's lifecycle status across all environmentsOptional MCP tools (enhance depth):
find-stale-flags — find flags that are candidates for cleanup, sorted by stalenessget-flag-health — get combined health view for a single flag (merges status + config)check-removal-readiness — detailed safety check for a specific flagBefore diving into flag data, establish context:
projectKey with the user. If they haven't specified one, ask.Adapt your approach to the user's goal:
For a broad audit:
list-flags scoped to a critical environment (default to production).state (active, inactive, launched, new) to segment the landscape.type (temporary vs permanent) — temporary flags are the primary cleanup targets.For cleanup planning:
find-stale-flags — this is the most efficient entry point. It returns a prioritized list of cleanup candidates sorted by staleness, categorized as:
never_requested — created but never evaluated (possibly abandoned)inactive_30d — no SDK evaluations in the specified periodlaunched_no_changes — fully rolled out, no recent changesinactiveDays is 30. Increase for conservative cleanup (60, 90) or decrease for aggressive cleanup (7, 14).includeOnly is temporary. Set to all to include permanent flags.For a targeted investigation:
get-flag-health for a single-flag deep dive. It merges status data with configuration context in one call, returning lifecycle state, last-requested timestamp, targeting summary, age, and whether it's temporary.get-flag for the full configuration including rules, targets, and fallthrough details.For flags that need deeper investigation, assess health signals. See Flag Health Signals for the full interpretation guide.
Key signals to evaluate:
| Signal | What it tells you |
|---|---|
| Lifecycle state | Where the flag is in its journey (new → active → launched → inactive) |
| Last requested | When an SDK last evaluated this flag — staleness indicator |
| Targeting complexity | Number of rules and targets — removal complexity indicator |
| Cross-environment consistency | Whether the flag behaves the same everywhere |
| Flag age + temporary status | Old temporary flags are strong cleanup candidates |
Use get-flag-status-across-envs to check if a flag is consistent across environments. A flag inactive in production but active in staging tells a different story than one inactive everywhere.
Group flags into actionable categories:
If the user wants to know whether a specific flag can be removed, use check-removal-readiness. This tool orchestrates multiple API calls in parallel and returns a structured verdict:
safe — No blockers or warnings. Proceed with cleanup.caution — Warnings exist (code references, expiring targets, permanent flag type). Present and let the user decide.blocked — Hard blockers (dependent flags, active requests, targeting rules). Must resolve first.See Removal Readiness Checklist for the full details on interpreting each signal.
Structure your response based on what the user asked for:
For audits: Lead with a summary (total flags, breakdown by state and type), then highlight what needs attention, then provide specific recommendations.
For specific flags: Lead with the verdict (healthy / needs attention / ready to remove), then support it with the signals you found.
For cleanup planning: Lead with the count of cleanup candidates, prioritize by confidence (safest removals first), and link to the cleanup workflow for execution.
60000 means 60%. Always convert to human-readable percentages.Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
launchdarkly-flag-discovery reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend launchdarkly-flag-discovery for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for launchdarkly-flag-discovery matched our evaluation — installs cleanly and behaves as described in the markdown.
We added launchdarkly-flag-discovery from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
We added launchdarkly-flag-discovery from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend launchdarkly-flag-discovery for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in launchdarkly-flag-discovery — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
launchdarkly-flag-discovery has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in launchdarkly-flag-discovery — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
launchdarkly-flag-discovery fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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