klingai-hello-world

Create your first Kling AI video generation with a minimal working example. Use when learning Kling AI or testing your setup. Trigger with phrases like 'kling ai hello world', 'first kling video', 'klingai quickstart', 'test klingai'.

Quality

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Does it follow best practices?

Impact

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No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

77%

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 clear, validated workflow, but it underuses its own bundle by duplicating reference material inline instead of linking out, which hurts both conciseness and progressive disclosure.

Suggestions

Keep one minimal example inline (e.g. Python) and replace the second with a link to references/minimal-typescript-example.md and references/curl-example.md to remove duplication.

Add a clearly signaled reference section linking to errors.md and examples.md rather than restating error handling and examples in the body.

Move the full response-shape and status-value tables into a reference file, keeping only the essentials inline.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient and avoids explaining concepts Claude already knows, but it inlines two near-complete language examples (Python and Node.js) performing the same create-poll cycle, duplicating content that also lives in references/minimal-python-example.md and minimal-typescript-example.md — it could be tightened by keeping one inline and linking the rest.	2 / 3
Actionability	Both code blocks are fully executable, copy-paste ready, with real endpoints, auth, request payloads, and response parsing — matching the top anchor for concrete, executable guidance.	3 / 3
Workflow Clarity	The create-poll-download cycle is explicitly sequenced (Step 1 create task, Step 2 poll until complete) with a status-check validation loop and explicit succeed/failed branching, supported by a Common First-Run Issues recovery table.	3 / 3
Progressive Disclosure	The body is well-sectioned, but it never links to the bundle reference files (curl-example.md, errors.md, examples.md, minimal-*-example.md) and instead duplicates their example/error content inline, fitting the "references present but not clearly signaled; content that should be separate is inline" anchor.	2 / 3
	Total	10 / 12 Passed

Description

80%

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 cleanly answers both what and when with strong, natural trigger phrases and a distinct niche. Its main weakness is second-person voice plus a single stated action, which caps specificity.

Suggestions

Rewrite in third person to avoid the voice penalty, e.g. "Creates a first Kling AI video generation via a minimal working example."

List two or three concrete actions (e.g. authenticate via JWT, submit a text2video task, poll for the result URL) to lift specificity from a single action to multiple concrete actions.

Dimension	Reasoning	Score
Specificity	The description names the Kling AI video-generation domain and one concrete action ("Create your first Kling AI video generation with a minimal working example"), which is base-level 2, but it uses second-person voice ("your first", "your setup") and lists only a single action rather than multiple concrete actions, triggering the voice penalty and keeping it below 2.	1 / 3
Completeness	It explicitly answers both what ("Create your first Kling AI video generation with a minimal working example") and when ("Use when learning Kling AI or testing your setup. Trigger with phrases like...") with explicit triggers, hitting the top anchor.	3 / 3
Trigger Term Quality	It provides good coverage of natural phrases a user would say — "kling ai hello world", "first kling video", "klingai quickstart", "test klingai" — plus "learning Kling AI or testing your setup", matching the top anchor for natural keyword coverage.	3 / 3
Distinctiveness Conflict Risk	Kling AI video generation is a clear niche with distinct, product-specific trigger phrases ("kling ai hello world", "klingai quickstart"), making it unlikely to fire for the wrong skill.	3 / 3
	Total	10 / 12 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Commit: 1628598

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

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