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klingai-job-monitoring

Track and monitor Kling AI video generation task status. Use when building dashboards, tracking batch jobs, or debugging stuck tasks. Trigger with phrases like 'klingai job status', 'kling ai monitor', 'track klingai task', 'klingai progress'.

72

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

80%

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

The content is lean and highly actionable with executable polling, batch-tracking, and stuck-detection code, but it underuses its own bundle: six reference files are orphaned (never linked from the body) and the inline code duplicates them. Batch-operation error handling is present but passive, lacking retry/escalation feedback loops.

Suggestions

Link the existing reference files from the body (e.g. under an Advanced/References section: "Job tracker class: see references/job-tracker-class.md"; "Error handling: see references/errors.md") so the overview points one level deep instead of duplicating their content inline.

Move the full BatchTracker class and polling implementation into references/ and keep SKILL.md as a concise overview + quick-start snippet, reducing the inline wall of code.

Add an active feedback loop for batch failures — retry with backoff, escalate stuck tasks, or surface a re-submit step — rather than printing-and-continuing, to satisfy the rubric's validation requirement for batch operations.

DimensionReasoningScore

Conciseness

The body goes straight into a lifecycle table and executable code with minimal prose, does not explain concepts Claude already knows (e.g. JWT, video generation), and every section earns its tokens — matching the lean/efficient anchor.

3 / 3

Actionability

Provides fully executable Python with real imports, real endpoints, JWT auth, and a complete runnable batch-monitor loop — copy-paste ready rather than pseudocode.

3 / 3

Workflow Clarity

A clear sequence exists (submit → poll → update → report → detect-stuck) with status checkpoints and a timeout, but for batch operations the error handling is passive (print-and-continue in update_all, warn-only detect_stuck) with no retry or escalation feedback loop, capping it at 2 per the rubric's batch-operation guidance.

2 / 3

Progressive Disclosure

The body is organized into sections, but six reference files exist (job-tracker-class.md, polling-monitor.md, batch-job-monitoring.md, dashboard-view.md, errors.md, examples.md) and none are linked or signaled from the body, while the tracker class and polling code are kept inline duplicating those files — content that should be separate is inline and references are unsignaled.

2 / 3

Total

10

/

12

Passed

Description

100%

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 concise, uses third-person voice, names concrete capabilities, and supplies both an explicit "Use when" clause and natural trigger phrases, making it clearly distinguishable and well-targeted. It is among the stronger examples in the rubric.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Track and monitor Kling AI video generation task status", "building dashboards", "tracking batch jobs", "debugging stuck tasks" — matching the anchor for listing multiple specific concrete actions rather than vague language.

3 / 3

Completeness

Clearly states what it does ("Track and monitor Kling AI video generation task status") and when to use it ("Use when building dashboards, tracking batch jobs, or debugging stuck tasks. Trigger with phrases like...") with explicit triggers, satisfying both what and when.

3 / 3

Trigger Term Quality

Explicit natural trigger phrases ("'klingai job status'", "'kling ai monitor'", "'track klingai task'", "'klingai progress'") are terms a user would plausibly say, giving good coverage rather than jargon.

3 / 3

Distinctiveness Conflict Risk

Kling AI video job monitoring is a narrow niche with distinctive "klingai"/"kling ai" triggers, making it unlikely to fire for unrelated skills.

3 / 3

Total

12

/

12

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

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
Reviewed

Table of Contents

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