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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'.

68

Quality

83%

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

72%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 body is highly actionable with executable code, but it inlines large implementations that overlap with the reference bundle without linking to it, and its batch workflow lacks validation checkpoints.

Suggestions

Add explicit validation/retry checkpoints to the batch monitor loop (e.g. verify task_id was returned, re-query on transient API errors, confirm terminal states) to lift workflow clarity above the batch cap of 3.

Replace the inlined BatchTracker and dashboard code with pointers to references/job-tracker-class.md, references/batch-job-monitoring.md, and references/dashboard-view.md so the body stays an overview with one-level-deep references.

Trim redundant docstrings, inline comments, and print formatting in the polling example to tighten token efficiency.

DimensionReasoningScore

Conciseness

Mostly lean and code-forward with minimal framing prose, though docstrings, comments, and print formatting add some tokens that could be trimmed.

4 / 5

Actionability

Provides fully executable, copy-paste-ready Python covering single-task polling, batch tracking, and stuck-task detection across the documented endpoints.

5 / 5

Workflow Clarity

A batch monitor loop is sequenced with stuck-task detection, but there are no validation/verification checkpoints before or during the batch submit-and-monitor operation; the batch-operation feedback-loop cap applies.

3 / 5

Progressive Disclosure

Substantial tracker/monitor/dashboard code is inlined in the body while parallel implementations exist in ./references, yet the body never signals or links to those bundle files, leaving navigation absent.

3 / 5

Total

15

/

20

Passed

Description

95%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.

A strong, third-person description with explicit what/when structure and natural trigger phrases. Coverage of actions and triggers is comprehensive with only minor specificity gaps.

DimensionReasoningScore

Specificity

Names the domain ('Kling AI video generation task status') and several concrete actions ('building dashboards, tracking batch jobs, debugging stuck tasks'), with only minor coverage gaps.

4 / 5

Completeness

Explicitly answers both 'what' (track and monitor task status) and 'when' via a 'Use when...' clause plus concrete trigger phrases, in third person.

5 / 5

Trigger Term Quality

Lists natural trigger phrases with synonyms ('klingai job status', 'kling ai monitor', 'track klingai task', 'klingai progress') covering the natural phrasings a user would say.

5 / 5

Distinctiveness Conflict Risk

Scoped narrowly to Kling AI job monitoring with distinct triggers, presenting minimal overlap risk with other skills.

5 / 5

Total

19

/

20

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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