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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.

68

Quality

83%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Risky

Do not use without reviewing

SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

This is a well-structured, highly actionable skill with a clear 5-step workflow and strong verification/troubleshooting guidance. Its main weaknesses are moderate verbosity in explanatory sections and the absence of the referenced bundle file (sdk-track-patterns.md), which the skill relies on heavily for per-language details. The workflow design with confirmation checkpoints and error recovery is a notable strength.

Suggestions

Provide the referenced 'references/sdk-track-patterns.md' bundle file, since the skill references it four times and it's critical for per-language implementation details.

Trim the 'Important Context' section — items like event buffering behavior and flush() timing are SDK documentation details that could be condensed to 2-3 bullet points or moved to the reference file.

DimensionReasoningScore

Conciseness

The skill is mostly efficient and well-structured, but includes some unnecessary explanation (e.g., the 'Important Context' section explains concepts like event buffering and flush behavior that Claude would know from SDK docs). The workflow steps are reasonably tight but could be trimmed in places — for instance, the 'Find the Right Placement' section's example dialogue and the detailed troubleshooting table add length that's partially justified but somewhat verbose.

2 / 3

Actionability

The skill provides concrete, executable code examples for both server-side and client-side SDKs, specific MCP tool invocations, a clear troubleshooting table with specific checks, and exact patterns to follow. The guidance is specific enough to be copy-paste ready and covers edge cases like value metrics, wrapper patterns, and context matching.

3 / 3

Workflow Clarity

The 5-step workflow is clearly sequenced with explicit validation in Step 5, including a troubleshooting checklist for when verification fails. The workflow includes a confirmation checkpoint in Step 3 before writing code, and the verify step has a clear feedback loop (check → diagnose from table → fix → retry). The skip condition in Step 2 is also well-handled.

3 / 3

Progressive Disclosure

The skill references 'references/sdk-track-patterns.md' multiple times for detailed per-language examples, which is good progressive disclosure design. However, no bundle files were provided, meaning the referenced file doesn't actually exist in the bundle, which undermines the reference structure. The main content is well-organized with clear sections but the Important Context section could arguably be split out.

2 / 3

Total

10

/

12

Passed

Description

89%

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

This is a well-crafted skill description that clearly identifies its niche (LaunchDarkly metric event instrumentation) and provides strong trigger guidance with a well-formed 'Use when...' clause covering multiple natural phrasings. Its main weakness is that the 'what' portion is somewhat narrow, describing only one concrete action (adding a track() call) rather than elaborating on related sub-tasks like SDK setup, event verification, or payload configuration.

Suggestions

Expand the capability description to list additional concrete actions beyond just adding a track() call, such as configuring event payloads, verifying event delivery, or selecting the correct SDK method for the language.

DimensionReasoningScore

Specificity

The description names the domain (LaunchDarkly metric events) and a specific action (adding a track() call), but it only describes one concrete action rather than listing multiple specific capabilities like code placement, SDK configuration, or event verification.

2 / 3

Completeness

Clearly answers both 'what' (instrument a LaunchDarkly metric event by adding a track() call) and 'when' (explicit 'Use when...' clause with multiple trigger scenarios including wiring up events, instrumenting actions, adding tracking, and confirming event flow).

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms: 'instrument', 'metric event', 'track() call', 'wire up an event', 'add tracking', 'LaunchDarkly', and 'event is flowing'. These are terms users would naturally use when requesting this kind of work.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with a clear niche: LaunchDarkly-specific metric instrumentation via track() calls. The combination of 'LaunchDarkly', 'metric', and 'track()' makes it very unlikely to conflict with generic analytics or other feature flag skills.

3 / 3

Total

11

/

12

Passed

Validation

100%

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

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
launchdarkly/ai-tooling
Reviewed

Table of Contents

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