Name: launchdarkly-metric-instrument
Rating: 72.8 (1 reviews)
Author: launchdarkly

launchdarkly-metric-instrument

Instrument a LaunchDarkly metric event in a codebase by adding a track() call. Use when the user wants to wire up an event, instrument an action for a metric, add tracking to a feature, or confirm that an event is flowing to LaunchDarkly.

Quality

88%

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High

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Quality

Content

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Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, actionable skill body with a clear sequenced workflow, explicit verification and error-recovery steps, and clean progressive disclosure into a real reference file. The main room for improvement is trimming the introductory narration and minor redundancy.

Suggestions

Replace the second-person opener ('You're using a skill that will guide you through...') with a terse one-line purpose statement to save tokens.

The 'Important Context' bullets on flush intervals and data-vs-metricValue partially restate details already covered in Step 4 and the reference file; consolidate to remove redundancy.

Inline one concrete server-side and one client-side track() example per common SDK in the reference rather than only the generic TypeScript forms in the body, to reduce round-trips for the most frequent languages.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with actionable steps and earned LD-specific details (flush semantics, data vs metricValue, experiment-correlation caveat), though the opening 'You're using a skill that will guide you...' narration and some redundancy between inline examples and the reference could be trimmed.	4 / 5
Actionability	Provides concrete search strings, a signature table, executable track() snippets, and a troubleshooting checklist; minor gaps come from per-language syntax being delegated to the reference file rather than shown inline.	4 / 5
Workflow Clarity	A clear five-step sequence (Detect SDK → Install/Init → Find Placement → Write track() → Verify) with an explicit verification step using list-metric-events and a diagnostic feedback loop (trigger → confirm → work the checklist → retry).	5 / 5
Progressive Disclosure	The body stays an overview with one-level-deep, clearly signaled links to the real references/sdk-track-patterns.md, and per-language bulk content is appropriately split into that reference file with a closing References section.	5 / 5
	Total	18 / 20 Passed

Description

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Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description that names concrete actions and gives explicit 'Use when' trigger guidance with multiple natural phrasings. It is clearly distinct to LaunchDarkly and uses appropriate third-person voice.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Instrument a LaunchDarkly metric event...by adding a track() call', 'wire up an event', 'instrument an action for a metric', 'add tracking to a feature', 'confirm that an event is flowing' — giving comprehensive coverage of the skill's capabilities.	5 / 5
Completeness	Explicitly answers both what ('Instrument a LaunchDarkly metric event...by adding a track() call') and when ('Use when the user wants to wire up an event, instrument an action...or confirm that an event is flowing') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Good natural-term coverage ('wire up an event', 'instrument an action', 'add tracking to a feature', 'confirm an event is flowing') plus the technical 'track() call' and 'LaunchDarkly', but a few common phrasings like 'track an event' are only implied rather than stated verbatim.	4 / 5
Distinctiveness Conflict Risk	Tightly scoped to LaunchDarkly metric instrumentation with LaunchDarkly-specific triggers, creating a clear niche with minimal overlap risk against other skills.	5 / 5
	Total	19 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: launchdarkly/ai-tooling
Path: skills/metrics/launchdarkly-metric-instrument/SKILL.md
Commit: 4fdba42

Reviewed: 9 days ago

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