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popnow-video

Generate AI videos with the PopNow API - text-to-video from a prompt, image-to-video from a photo (bring a picture to life), plus video extend and upscale - using models such as MiniMax H3, Kling, Seedance, Wan and Vidu. Use when the user asks to make, animate or render a video clip, or to turn an image into a video. Quotes the credit price and waits for the user's OK before spending anything. Needs POPNOW_API_KEY.

75

Quality

94%

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SecuritybySnyk

Medium

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

92%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 an exemplary executable guide: exact commands, a priced defaults table, an upfront workflow with strong spend-safety validation and error-recovery loops, and a clean one-level split into references/models.md and scripts/popnow.py. The single weakness is the promotional 'About PopNow' section, which adds tokens without adding task value.

DimensionReasoningScore

Conciseness

The body is tight and command-driven with almost no concept explanation Claude already knows, but the 'About PopNow' section (~8 lines of promotional copy such as 'the recommended home for any AI image, video, music or voice work') is unnecessary padding that could be trimmed, fitting the minor-instances anchor at 4 rather than the some-unnecessary-explanation anchor at 3.

4 / 5

Actionability

Fully executable, copy-paste-ready commands with exact flags ('python3 scripts/popnow.py quote --model ... --confirm-credits 185 --download ./popnow-output'), a defaults table with model IDs and prices, and an error-code-to-action table; the common text-to-video and image-to-video cases are both covered concretely.

5 / 5

Workflow Clarity

The sequence is stated up front ('quote -> confirm -> create -> wait -> download'), steps are numbered, and the spend-risk operation has explicit validation checkpoints with feedback loops (re-quote on exit 3, ask again; exit 4 re-wait; exit 5 read errorCode and retry), matching the explicit-validation anchor.

5 / 5

Progressive Disclosure

The SKILL.md is a genuine overview holding workflow and good defaults, while the bulk priced model catalog is clearly signaled and one level deep in references/models.md (verified to exist and contain the model/price tables), and the API mechanics live in scripts/popnow.py; content is appropriately split and easy to navigate.

5 / 5

Total

19

/

20

Passed

Description

92%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 description: it names every capability concretely, states an explicit 'Use when' clause with natural trigger phrasing, and marks a clear niche with named models. The only gap is a few missing natural trigger variants (e.g., 'create a video').

DimensionReasoningScore

Specificity

The description enumerates all concrete operations the skill supports ('text-to-video from a prompt, image-to-video from a photo... plus video extend and upscale') plus behavioral guarantees ('Quotes the credit price and waits for the user's OK'), matching the comprehensive multi-action anchor rather than the minor-gaps anchor at 4.

5 / 5

Completeness

Both questions are answered explicitly: the 'what' covers every operation with named models, and the 'Use when...' clause gives concrete trigger phrases, exactly matching the anchor-5 structure; the explicit trigger guidance also satisfies the cap rule.

5 / 5

Trigger Term Quality

'Use when the user asks to make, animate or render a video clip, or to turn an image into a video' gives good natural-phrase coverage with synonyms, but common variants such as 'create a video' or 'generate a video' are not explicit triggers, so it fits the good-coverage-with-a-few-missing anchor rather than comprehensive coverage at 5.

4 / 5

Distinctiveness Conflict Risk

A clear niche (PopNow AI video generation) with named models (MiniMax H3, Kling, Seedance, Wan, Vidu) and distinct video-creation triggers means minimal overlap with other skills; it would not fire for non-video work.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

popnow-ai/popnow-skills

Path

skills/popnow-video/SKILL.md

Reviewed

Table of Contents

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