Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Bilal140202/the-lord-of-the-skills --skill feature-flags-launchdarkly-flag-cleanupgit clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/feature-flags-launchdarkly-flag-cleanup)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/feature-flags-launchdarkly-flag-cleanup"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/feature-flags-launchdarkly-flag-cleanup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/feature-flags-launchdarkly-flag-cleanup"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/feature-flags-launchdarkly-flag-cleanup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.01987 |
| Opus 5 | $0.00026 | $0.00993 |
| Sonnet 5 | $0.00011 | $0.00397 |
| Haiku 4.5 | $0.00005 | $0.00199 |
Grade A, and why
launchdarkly-flag-cleanup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LaunchDarkly Flag Cleanup
You're using a skill that will guide you through safely removing a feature flag from a codebase while preserving production behavior. Your job is to explore the codebase to understand how the flag is used, query LaunchDarkly to determine the correct forward value, remove the flag code cleanly, and verify the result.
If you haven't already identified which flag to clean up, use the flag discovery skill first to audit the landscape and find candidates.
Prerequisites
This skill requires the remotely hosted LaunchDarkly MCP server to be configured in your environment.
Required MCP tools:
check-removal-readiness: detailed safety check (orchestrates flag config, cross-env status, dependencies, code references, and expiring targets in parallel)get-flag: fetch flag configuration for a specific environment
Optional MCP tools:
archive-flag: archive the flag in LaunchDarkly after code removaldelete-flag: permanently delete the flag (irreversible, prefer archive)
Core Principles
- Safety First: Always preserve current production behavior.
- LaunchDarkly as Source of Truth: Never guess the forward value. Query the actual configuration.
- Follow Conventions: Respect existing code style and structure.
- Minimal Change: Only remove flag-related code. No unrelated refactors.
Workflow
Step 1: Explore the Codebase
Before touching LaunchDarkly or removing code, understand how this flag is used in the codebase.
- Find all references to the flag key. Search for the flag key string (e.g.,
new-checkout-flow) across the codebase. Check for:- Direct SDK evaluation calls (
variation(),boolVariation(),useFlags(), etc.) - Constants/enums that reference the key
- Wrapper/service patterns that abstract the SDK
- Configuration files, tests, and documentation
- See SDK Patterns for the full list of patterns by language
- Direct SDK evaluation calls (
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 180 lines · 53 tokens per session scan A ca993873eed9
launchdarkly-flag-cleanup is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (4 stars, last pushed 6d ago), licensed MIT. It adds 53 tokens to every session and 1,987 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-06.
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