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 metrics-launchdarkly-metric-choosegit 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/metrics-launchdarkly-metric-choose)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/metrics-launchdarkly-metric-choose"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/metrics-launchdarkly-metric-choose/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/metrics-launchdarkly-metric-choose"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/metrics-launchdarkly-metric-choose.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 | $0.00078 | $0.02165 |
| Opus 5.5 | $0.00031 | $0.00866 |
| Sonnet 5.5 | $0.00016 | $0.00433 |
| Haiku 4.5 | $0.00008 | $0.00216 |
Grade A, and why
launchdarkly-metric-choose 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 1mo 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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LaunchDarkly Metric Choose
You're using a skill that helps users select the right metrics before setting up an experiment, guarded rollout, or release policy. Your job is to understand the feature context, surface what will auto-attach from existing project policies, inventory what's available and healthy, and produce a clear typed recommendation.
This skill is advisory. It does not create metrics, attach them to experiments, or configure rollouts. For those tasks, see the related skills at the end of this document.
Prerequisites
This skill requires the remotely hosted LaunchDarkly MCP server to be configured in your environment.
Required MCP tools:
list-metrics— inventory available metrics with their types and event keyslist-metric-events— check which event keys have recent activity
Optional MCP tools (enhance workflow):
list-release-policies— fetch project-level policies that configure which metrics auto-attach to guarded rollouts. Use this for the guarded rollout and release policy paths.
Workflow
Step 1: Identify the Context
Ask two questions upfront:
-
What is this for?
- (a) Experiment — testing a hypothesis with a flag variant
- (b) Guarded rollout — progressively rolling out a change with automatic regression detection
- (c) Release policy — creating or editing a project-wide policy that configures default metrics for all guarded rollouts matching certain conditions
-
What is the change?
- Flag key (if applicable)
- Plain-language description: "Rolling out a new checkout flow" / "Testing a new recommendation algorithm"
Step 2: Fetch Existing Configuration (Guarded Rollout and Release Policy only)
For experiments — skip this step. There is no pre-existing configuration to surface.
For guarded rollouts and release policy work, call list-release-policies first:
list-release-policies(projectKey)
Surface the results before making any recommendations:
Your project has 2 release policies:
Policy: "Production guardrails" (applies to: environment=production)
Auto-attaches to guarded rollouts:
✓ api-error-rate (count, LowerThanBaseline)
✓ p95-latency (value, LowerThanBaseline)
✓ [Metric group] Core Platform Health (3 metrics)
Policy: "Default" (applies to: all environments)
No metrics configured.
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.
- 1mo ago First seen · 187 lines · 78 tokens per session scan A b65664c7ebc2
launchdarkly-metric-choose is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 78 tokens to every session and 2,165 once invoked, about $0.0003 per session on Opus 5.5. 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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