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ai-video-gen

Generate AI videos from text prompts using multiple provider gateways. Use when: (1) Generating videos from text descriptions, (2) Creating AI-generated video clips for content production, (3) Image-to-video generation with a reference image, (4) Choosing between video generation providers (VEO, Kling, Sora, Runway, Seedance, MiniMax, Gemini Omni). Supports gateways: HeyGen API, fal.ai API, Kling official direct API, and the Gemini API (Gemini Omni Flash).

67

Quality

82%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

65%

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 complete executable examples and a clear async polling sequence, but it is verbose with redundant curl repetitions and keeps a large inline API reference despite pointing to 'Layer 3' files that do not exist in the bundle. Tightening duplication and moving the full reference into actual referenced files would lift the weaker dimensions.

Suggestions

Consolidate the repeated HeyGen curl examples — show one canonical request once and drop the duplicate in the intro and Usage Examples, or differentiate each example by intent rather than restating the same payload.

Split the full endpoint/field/provider API reference into an actual referenced file (e.g. references/heygen-api.md) and link to it from the overview, rather than keeping it all inline and referencing 'Layer 3' guides that are not present in the bundle.

Add an explicit retry/feedback step for the 'failed' and 'not_found' polling states (e.g. re-submit or surface the error and offer corrective options) so the async generation workflow has a true validation->fix->retry loop.

DimensionReasoningScore

Conciseness

The ~310-line body is mostly lean reference material (tables and code) with no concept-padding, but it repeats the HeyGen curl example multiple times (intro, Execute, Usage Examples) and provides full TypeScript, Python, and a polling-loop variant of the same endpoint, so it could be tightened; this fits the 'mostly efficient but could be tightened' anchor rather than the score-3 'every token earns its place'.

2 / 3

Actionability

Provides fully executable bash, TypeScript, and Python code with exact endpoints, request-field and provider-value tables, and concrete response formats — copy-paste ready, matching the 'fully executable code/commands; specific examples; copy-paste ready' anchor.

3 / 3

Workflow Clarity

The default workflow is clearly sequenced (submit → execution_id → poll every 10s → video_url) with a polling loop that checks completed/failed/not_found/timeout, but on failure it throws rather than offering a validate-and-retry feedback loop; per the rubric's scoring notes, a missing feedback loop for a batch/async generation operation caps workflow clarity at 2.

2 / 3

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are absent), yet the body keeps a full inline API reference (endpoints, fields, providers, three language examples) that the rubric says 'could be in a separate file', and the cited 'Layer 3 gemini-omni' / 'seedance-2-0' guides are not real files — fitting the 'content that should be separate is inline' anchor.

2 / 3

Total

9

/

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 strong: it states concrete capabilities, lists explicit 'Use when' triggers covering four scenarios, names the relevant providers, and uses third-person voice. It cleanly satisfies all four dimensions at the top of the scale.

DimensionReasoningScore

Specificity

Names multiple concrete actions — 'Generate AI videos from text prompts', 'Image-to-video generation with a reference image', and choosing between named providers — matching the 'lists multiple specific concrete actions' anchor, not the score-2 anchor of naming only a domain and some actions.

3 / 3

Completeness

Explicitly answers both 'what' (opening sentence) and 'when' via a numbered 'Use when: (1)...(2)...(3)...(4)...' clause, matching the anchor for clearly answering what AND when with explicit triggers.

3 / 3

Trigger Term Quality

Covers natural user terms — 'videos', 'video clips', 'image-to-video', and provider names (VEO, Kling, Sora, Runway, Seedance, MiniMax) — giving good coverage of phrasings users would actually say rather than only technical jargon.

3 / 3

Distinctiveness Conflict Risk

Targets a clear niche (AI video generation through specific gateways) with distinct provider-named triggers, making it unlikely to fire for unrelated skills.

3 / 3

Total

12

/

12

Passed

Validation

81%

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

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

Total

13

/

16

Passed

Repository
calesthio/OpenMontage
Reviewed

Table of Contents

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