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launchdarkly-flag-qualitative-feedback-setup

Integrate LaunchDarkly qualitative user feedback into a JavaScript/TypeScript codebase. Guides framework and design system detection, builds the sendFeedback utility and feedback widget matching existing project patterns. Use when the user wants to add a Give Feedback widget, collect user sentiment tied to feature flags, set up feedback collection, or wire up the $ld:feedback tracking event.

70

Quality

88%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

81%Weight 40%Scale 1-5

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

The content is highly actionable with a well-sequenced, gated workflow and good reference structure. The main weakness is conciseness — several sections restate the same guidance and could be consolidated.

Suggestions

Consolidate 'Core Principles' and 'What NOT to Do' into a single list to remove overlap, since both cover 'don't ship the unstyled template' and 'one entry point per screen'.

Trim or move 'Example Flows' into a reference file, since it restates the workflow steps already documented above and adds length without new executable detail.

Remove the restated wizard framing from the opening paragraph — the Step 0 intro block already conveys the same information to the user.

DimensionReasoningScore

Conciseness

The body is action-dense but ~340 lines with redundancy: the intro re-states the wizard framing, 'What NOT to Do' overlaps 'Core Principles', and 'Example Flows' restate the workflow steps, so it could be tightened.

3 / 5

Actionability

Provides fully executable guidance: the 'client.track' event contract, real template files, a framework detection table, a design-system replacement table, a vanilla JS wiring snippet, and concrete search strings for verification.

5 / 5

Workflow Clarity

Steps 0–7 are clearly sequenced with explicit STOP gates (Checks 1–4), pre-condition checks, verification sub-steps, and feedback loops ('If not found, fix before proceeding'; 'If errors: fix and re-validate').

5 / 5

Progressive Disclosure

SKILL.md serves as the overview with clearly signaled one-level-deep links to real reference files (sendFeedback.ts, PopoverFeedback.tsx, InlineFeedback.tsx, SDK lists), though the overview itself is long.

4 / 5

Total

17

/

20

Passed

Description

92%Weight 40%Scale 1-5

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

The description is specific, trigger-rich, and clearly distinguishes the skill's niche. It answers both what and when with concrete, natural-language triggers.

DimensionReasoningScore

Specificity

Names the domain and multiple concrete actions: 'framework and design system detection', 'builds the sendFeedback utility and feedback widget matching existing project patterns', giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both 'what' (integrate feedback, build utility and widget) and 'when' via a concrete 'Use when...' clause with several trigger scenarios.

5 / 5

Trigger Term Quality

Strong natural trigger phrases like 'add a Give Feedback widget', 'collect user sentiment tied to feature flags', and 'wire up the $ld:feedback tracking event', but a few common synonyms (e.g. 'feedback form', 'user comments') are absent.

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche — LaunchDarkly qualitative feedback and the '$ld:feedback' event — with distinct triggers and minimal overlap risk with other skills.

5 / 5

Total

19

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 1 suspicious

Warning

Total

15

/

16

Passed

Repository
launchdarkly/ai-tooling
Reviewed

Table of Contents

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