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klingai-batch-processing

Process multiple video generation requests efficiently with Kling AI. Use when generating batches of videos or building content pipelines. Trigger with phrases like 'klingai batch', 'kling ai bulk', 'multiple videos klingai', 'klingai parallel generation'.

63

Quality

75%

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./plugins/saas-packs/klingai-pack/skills/klingai-batch-processing/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

68%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 complete, executable code, but it lacks a validated batch workflow and completely ignores the provided bundle files, inlining content that should be split out. Adding explicit verification checkpoints and linking the reference files would substantially raise the two lowest dimensions.

Suggestions

Add an explicit sequenced batch workflow with validation checkpoints: verify credentials/credits before submit (the cost estimator already exists), check per-task failure status, and retry failures — pulling retry logic from batch-with-retry-logic.md.

Link the existing bundle files from the body (e.g. a Reference section pointing to errors.md, csv-batch-input.md, batch-processor-class.md, examples.md) instead of leaving them un-referenced.

Promote one canonical batch approach in the body and move the alternate variants (asyncio, callbacks) into a reference file to reduce duplication.

DimensionReasoningScore

Conciseness

The body is mostly lean, executable code with minimal prose padding and assumes Claude's competence, but it inlines three overlapping batch approaches (sync, asyncio, callbacks) where one primary path plus pointers would be tighter, so it is not fully 5-lean.

4 / 5

Actionability

The code is fully executable with real endpoints, real JWT auth, and concrete parameters, covering submit, poll, collect, async, callbacks, and cost estimation in copy-paste-ready form across the common cases.

5 / 5

Workflow Clarity

The batch operation has an implicit submit->poll->collect sequence but no explicit validation checkpoints or feedback loops (no pre-submit credit/credential check, no failure-then-retry loop in the body), so per the batch-operation cap it cannot exceed 3.

3 / 5

Progressive Disclosure

Bundle files exist (batch-processor-class.md, batch-with-retry-logic.md, csv-batch-input.md, errors.md, examples.md) but the body never references any of them, and substantial code that belongs in those files is inlined, leaving references un-signaled and effectively buried.

2 / 5

Total

14

/

20

Passed

Description

82%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 well-formed: it clearly states the skill's purpose and gives explicit, fairly natural trigger phrases tied to a distinctive niche. The main weakness is specificity, where it states high-level actions rather than enumerating concrete operations.

Suggestions

Enumerate concrete operations (e.g. submit with rate-limited pacing, poll for completion, collect results, estimate credit cost) instead of the single high-level "Process multiple video generation requests" action.

Consider adding a more colloquial trigger phrase (e.g. "generate a bunch of kling videos") alongside the existing keyword-style triggers to improve naturalness.

DimensionReasoningScore

Specificity

Names the domain (Kling AI video generation) and a couple of concrete actions ("Process multiple video generation requests", "building content pipelines"), but does not enumerate several specific operations, so it stops at the 1-2 actions anchor rather than 4.

3 / 5

Completeness

It explicitly answers both "what" (process multiple video generation requests / build content pipelines) and "when" with concrete trigger phrases ("Use when generating batches... Trigger with phrases like..."), matching the top anchor.

5 / 5

Trigger Term Quality

Provides good keyword coverage with natural variations ("klingai batch", "kling ai bulk", "multiple videos klingai", "klingai parallel generation"), though "klingai parallel generation" leans toward jargon and coverage is not fully comprehensive of synonyms, keeping it just below 5.

4 / 5

Distinctiveness Conflict Risk

Scoped to Kling AI batch video generation with distinctive, brand-specific triggers, giving it a clear niche with minimal overlap risk against other skills.

5 / 5

Total

17

/

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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